Iris biometric recognition module and access control assembly

ABSTRACT

An iris biometric recognition module includes technology for capturing images of an iris of an eye of a person, whether the person is moving or stationary, and whether the person is located near the iris image capture device or at a distance from the iris image capture device. The iris biometric recognition technology can perform an iris matching procedure for, e.g., authentication or identity verification purposes. The iris biometric recognition module can be incorporated into, for example, a door lock assembly and other access controlled devices, mechanisms, and systems.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application claims priority to and the benefit of U.S. ProvisionalPatent Application Ser. No. 61/888,130, filed Oct. 8, 2013, which isincorporated herein by this reference in its entirety.

BACKGROUND

Many existing iris recognition-based biometric devices impose strictrequirements on the iris image capture process in order to meet theneeds of iris biometric analysis. For example, many existing devices canonly utilize images that have a clear, straight-on view of the iris. Inorder to obtain such images, existing devices typically require thehuman subject to be stationary and located very near to the iris imagecapture device.

BRIEF DESCRIPTION OF THE DRAWINGS

This disclosure is illustrated by way of example and not by way oflimitation in the accompanying figures. The figures may, alone or incombination, illustrate one or more embodiments of the disclosure.Elements illustrated in the figures are not necessarily drawn to scale.Reference labels may be repeated among the figures to indicatecorresponding or analogous elements.

FIG. 1 depicts a simplified block diagram of at least one embodiment ofan iris processor for biometric iris matching, including a pre-processoras disclosed herein;

FIG. 2 depicts a simplified block diagram of at least one embodiment ofthe pre-processor of the iris processor of FIG. 1;

FIG. 3A depicts a simplified graphical plot illustrating an effect ofcamera illumination on pupil and iris intensity as disclosed herein;

FIG. 3B depicts an illustration of a result of the operation of thepre-processor of FIG. 2;

FIG. 3C depicts an illustration of another result of the operation ofthe pre-processor of FIG. 2, with an alternate image;

FIG. 3D depicts a simplified illustration of yet another result of theoperation of the pre-processor of FIG. 2, with yet another alternateimage;

FIG. 4A depicts a simplified flow diagram for at least one embodiment ofa method for edge detection, which may be performed by the irisprocessor of FIG. 1;

FIG. 4B shows simplified examples of candidate pupil contour curves asdisclosed herein;

FIG. 4C depicts a simplified flow diagram for at least one embodiment ofa method for corneal distortion correction, which may be performed bythe iris processor of FIG. 1;

FIG. 4D illustrates a simplified result of correction for foreshorteningas disclosed herein;

FIG. 5 depicts a simplified block diagram of at least one embodiment ofa coding processor as disclosed herein;

FIG. 6 depicts a simplified example of at least one embodiment of amultiresolution iris code as disclosed herein;

FIG. 7 depicts a simplified block diagram of at least one embodiment ofa matching processor as disclosed herein;

FIG. 8 depicts a simplified example of at least one embodiment of aprocess for matching iris codes, which may be performed by the matchingprocessor of FIG. 7;

FIG. 9 is a simplified schematic depiction of a coarse-fine algorithm toestimate flow-field of an iris code, as disclosed herein;

FIG. 10 is a simplified flow diagram depicting at least one embodimentof a method for estimating flow field between two iris codes, asdisclosed herein;

FIG. 11 is a simplified flow diagram depicting at least one embodimentof a method for estimating flow field between two iris codes asdisclosed herein;

FIG. 12 depicts a simplified schematic diagram of at least oneembodiment of a computer system for implementing the iris processor ofFIG. 1, as disclosed herein;

FIG. 13 illustrates at least one embodiment of the iris processor ofFIG. 1 in an exemplary operating scenario, as disclosed herein;

FIG. 14 is a simplified view of at least one embodiment of an irisbiometric recognition-enabled access control assembly in an exemplaryoperating environment, as disclosed herein;

FIG. 15 is a simplified exploded perspective view of the access controlassembly of FIG. 14, shown in relation to a cut away portion of anaccess control structure, and including at least one embodiment of aniris biometric recognition module;

FIG. 16 is a simplified assembled perspective view of the iris biometricrecognition module of FIG. 15;

FIG. 17 is an exploded perspective view of the iris biometricrecognition module of FIG. 16;

FIG. 18 is a simplified schematic diagram showing components of an irisbiometric recognition module and an access control module in anenvironment of the access control assembly of FIG. 14;

FIG. 19 is a simplified flow diagram of at least one embodiment of amethod for performing iris biometric recognition-enabled access controlas disclosed herein, which may be performed by one or more components ofthe access control assembly of FIG. 14; and

FIG. 20 is a simplified block diagram of at least one embodiment of asystem including an iris biometric recognition module as disclosedherein.

DETAILED DESCRIPTION OF THE DRAWINGS

While the concepts of the present disclosure are susceptible to variousmodifications and alternative forms, specific embodiments thereof areshown by way of example in the drawings and are described in detailbelow. It should be understood that there is no intent to limit theconcepts of the present disclosure to the particular forms disclosed. Onthe contrary, the intent is to cover all modifications, equivalents, andalternatives consistent with the present disclosure and the appendedclaims.

Referring now to FIGS. 1-13, FIGS. 1-13 relate to subject matter that isshown and described in U.S. Utility patent application Ser. No.14/100,615, filed Dec. 9, 2013, which is incorporated herein by thisreference in its entirety.

FIG. 1 depicts a block diagram of an iris processor 100 for biometriciris matching in accordance with exemplary embodiments of the presentinvention. The iris processor 100 comprises a pre-processor 102, acoding processor 104 and a matching processor 106. The iris processor100 receives images as input, for example, input image 101 and outputs amatched iris 108 from a remote or local database. Those of ordinaryskill in the art would recognize that the database may be accessed as a“cloud” service, directly through an internet connection, or the like.The pre-processor 102, the coding processor 104 and the matchingprocessor 106 may execute on a single device, or on different devices,servers, cloud services or the like, as indicated by the dashed outlineof the iris processor 100. The iris processor 100 may be modular andeach processor may be implemented, e.g., on a single device, multipledevices, in the cloud as a service. Any of the components, e.g., thepre-processor 102, the coding processor 104, and the matching processor106, may be implemented or used independently of one another.

According to exemplary embodiments of the present invention, the inputimage 101 is an infrared image, and is captured by an infrared capturedevice (not shown in FIG. 1), coupled to the iris processor 100. Theinfrared capture device may be any type of infrared capture device knownto those of ordinary skill in the art. In other instances, the inputimage 101 is a red, green, blue (RGB) image, or the like. The inputimage 101 contains an eye with an at least partially visible iris andpupil and the iris processor 100 attempts to match that eye with an irisof an eye image in a local or remote database of eye images. Accordingto exemplary embodiments, irises are matched based on Hamming distancesbetween two coded iris images.

Initially, the input image 101 is processed by the pre-processor 102.The pre-processor 102 segments and normalizes the iris in the inputimage 101, where input image 101 may have variable iris/pupil andiris/sclera contrast, small eyelid openings, and non-frontal irispresentations. The result of the pre-processor 102 is a modified irisimage with clearly delineated iris boundaries and synthesizedquasi-frontal presentation. For example, if the iris in the input image101 is rotated towards the left, right, up or down, the pre-processor102 will synthesize an iris on the input image 101 as if it waspositioned directly frontally. Similarly, a frontally positioned pupilwill be synthesized on the skewed or rotated pupil of the input image101.

The coding processor 104 analyzes and encodes iris information from theiris image generated by the pre-processor 102 at a range of spatialscales so that structural iris information contained in the input image101 of varying resolution, quality, and state of focus can be robustlyrepresented. The information content of the resulting code will varydepending on the characteristics of input image 101. The code generatedby the coding processor 104 representing the input image 101 allowsspatial interpolation to facilitate iris code alignment by the matchingprocessor 106.

The output code from the coding processor 104 is coupled to the matchingprocessor 106. The matching processor 106 incorporates constrainedactive alignment of iris structure information between stored irisimages and captured iris codes generated from the input image 101 tocompensate for limitations in iris image normalization by thepre-processor 102. The matching processor 106 performs alignment byperforming local shifting or warping of the code to match the generatedcode with a stored iris code template based on estimated residualdistortion of the code generated by the coding processor 104. Accordingto some embodiments, a “barrel shift” algorithm is employed to performthe alignment. Accordingly, structural correspondences are registeredand the matching processor 106 compares the aligned codes to determinewhether a match exists. If a match is found, the matching processorreturns matched iris data 108.

The matched iris data 108 may be used in many instances, for example, toauthorize financial transactions. The pre-processor 102 may be anapplication executing on a mobile device, such as a mobile phone,camera, tablet, or the like. The pre-processor 102 on the mobile devicemay capture an image of a user's eye using the camera of the device,perform the pre-processing steps on the mobile device, and then transmita bundled and encrypted request to the coding processor 104, which maybe accessed via a cloud service on a remote server of, for example, afinancial institution. In other embodiments, the application on themobile device may also comprise the coding processor 104 and the iriscoding is performed on the mobile device. In some embodiments, thepre-processor 102 may be used in conjunction with an automated tellermachine (ATM), where a user is authorized via their iris being scannedand processed by the pre-processor 102. The pre-processor 102 may thenreside in the software of the ATM, or the ATM may supply the imagecaptured by the camera to a server where the pre-processor 102 isexecuted for pre-processing.

The coding processor 104 produces an iris code that is transmitted tothe matching processor 106. The matching processor 106 may be hosted ona server of a financial institution, or be a remote third party serviceavailable to multiple financial institutions for authenticating the userbased on their iris image. Once a user is authenticated, financialtransactions may be carried out between the user and the financialinstitutions. Similarly, the iris processor 100 may be used toauthenticate a user in any context, such as signing in to a socialnetwork, a messaging service or the like.

The iris processor 100 may be used, for example, for collecting andtargeting of marketing data based upon iris identification. For example,a customer in a grocery store can be detected and their iris can bestored in a local or remote database. If the customer enters the grocerystore again, or an associated store with which the iris information isshared, the store can build a profile of the customer, the items theymost often purchase, peruse, or the like by using iris detection andgaze tracking. These marketing profiles can be used by the store itselffor product placement, or may be used by third party marketing servicesas marketing data. In other embodiments, the customer profile can bematched with identifying information, and when the customer uses awebsite affiliated with the store, or a website, which has access to theiris data, the website identifies the customer and offers targetedmarketing to the customer.

The iris processor 100 may be used to authorize a cellular device user,determining whether the device is stolen or not, in conjunction withgeo-location data, or the like. In this embodiment, upon purchase of acellular device, the user may “imprint” their identity on the devicebased on their iris information so that others can be prevented fromusing the device if reported stolen. Authorization can also be extendedto the office or personal environments, where the iris processor 100 maybe used to determine whether an authorized or detected user has accessto a particular location. For example, in a secure office environment,taking photographs may be prohibited for the majority of employees, butoverriding this prohibition and enabling the camera is available toauthorized employees. The employee's mobile device will be used tocapture an image of the employee, and the iris processor 100 will matchthe iris of the employee to extract an employee profile, whichdelineates the authorizations for this employee.

In the medical field, the iris processor 100 may be used to determinewhether a person accessing particular medical resources, such asmedicine, devices, or the like, are permitted to access these resources.The iris processor 100 can be coupled with a recording device, whichcaptures video of those accessing a medicine cabinet, for example, andwhether they are authorized to take medical resources from the cabinet.

The iris processor 100 may be used as a security system andauthentication device by a small company with limited resources. Bysimply coupling a camera or other image capturing device to anelectro/mechanical locking system, the company can limit access todoors, offices, vaults, or the like, to only authorized persons. Theiris codes produced by the coding processor 104 can be used toauthorize, for example, airline boarding passes. On purchase of a travel(airline, train, bus, etc.) ticket, the coding processor 104 generatesan iris code of the purchaser and saves the iris code for imprinting onthe boarding pass. When a traveler is boarding an airplane, bus ortrain, the carrier may invoke the matching processor 106 to match theiris code on the boarding pass with the iris code produced by thetraveler presenting the boarding pass. If there is a match, the traveleris allowed to board the bus, train or airplane.

FIG. 2 depicts a block diagram of the pre-processor of the irisprocessor 100 in accordance with exemplary embodiments of the presentinvention. The pre-processor receives the input image 101 and outputs arectified iris image 220. The rectified iris image 220 corrects foruncontrolled capture scenarios such as ambient illumination conditions,varied illumination geometries, reduced eyelid opening area,presentation angle (obliquity), or the like. The rectified iris image220 corrects for various nonconformities.

The pre-processor 200 comprises a segmentation module 202 and acorrection module 204. The segmentation module 202 further comprises apupil segmentation module 206, an iris segmentation module 208 and anedge detection module 209. The segmentation module 202 corrects an inputimage for low-contrast pupil and iris boundaries. The image produced bythe segmentation module 202 is then coupled to the correction module 204for further correction. The correction module 204 comprises a tiltcorrection module 210 and a corneal correction module 212. The detailsof the segmentation module 202 are described below.

FIG. 3A illustrates that varying illumination geometry produces varyingpupil appearance. FIG. 3A illustrates measurement of pupil-irisintensity difference as a function of distance, e.g., 1 and 2 meters,pupil size, e.g., 2.4 mm and 4.0 mm, and camera/illuminator distance,e.g., 6 to 16 cm. As the camera/illuminator distance increases, thepupil iris intensity decreases. The contrast of the pupil varies greatlyas a function of distance between camera and subject as well asfunctions of illuminator geometry and pupil diameter. The variation withdistance is due to the fact that the angular distance between theilluminator and camera axes are greater at short range (e.g., 1 m) thanat longer distances. As the illuminator and camera axes get closer, morelight that is reflected from the retina back out through the pupil iscaptured by the camera lens. This causes red eye in ordinary photographsand bright pupils in infrared photography. An exemplary illuminator isdescribed in U.S. Pat. No. 7,542,628 to Matey entitled “Method andApparatus for Providing Strobed Image Capture” filed on Jan. 19, 2006,and U.S. Pat. No. 7,657,127 to Matey entitled “Method and Apparatus forProviding Strobed Image Capture” filed on Apr. 24, 2009, each of whichis incorporated herein by this reference in its entirety.

The segmentation module 202 and the correction module 204 may be used,for example, in the medical field, in targeted marketing, customertracking in a store, or the like. For example, pupil and iris insertionmay be performed by the pre-processor 102, as described further withrespect to FIGS. 2 and 3A-3D, in the medical field as a diagnostic toolfor diagnosing diseases that a person might have based on their irisprofiles.

FIG. 3B illustrates an example of iris and pupil boundary matching inaccordance with exemplary embodiments of the present invention.According to some embodiments, iris diameters are normalized by the irissegmentation module 208. Size normalization is performed using a rangeestimate derived from an autofocus setting of the camera taking theimage. The image 300 shows the pupil boundary 304 calculated by thepupil segmentation module 206. The pupil segmentation module 206 theninserts an artificial dark pupil in the pupil boundary 304 in image 300.Image 300 is then coupled to the iris segmentation module 208, whichcalculates the iris boundary. FIGS. 3C and 3D illustrate examples ofinserted artificial pupils and iris boundaries. In FIG. 3C, input image320 is coupled to the pre-processor 200. The input image 320 is thensegmented by pupil segmentation module 206 to calculate a pupil boundaryregion 326. The pupil segmentation module then inserts an artificialblack colored pupil in the pupil boundary region 326. Additionally,oblique irises and pupils are warped to be circular. The insertion of anartificial pupil in the pupil boundary region 326 may be used, forexample, to remove red-eye effects in an image captured by a camera. Thesegmentation module 202 can be used to segment the pupil and iris areas,and the pupils may be red-eye corrected by insertion of the artificialpupil. This process of segmentation and warping is described in moredetail below.

FIG. 3D shows a similar process but on a downward facing iris in image350. The pupil boundary 356 is still detected despite being occluded bythe eyelid in image 352. The pupil and iris are both warped to formcircular regions to aid in segmentation. The pupil segmentation module206 inserts a black disk/artificial pupil in the image 352 and couplesthe image 352 to the iris segmentation module 208. The iris segmentationmodule 208 determines an iris boundary 358. Ultimately, the iris andpupil boundaries are corrected for various lighting conditions andpresented in image 354, where region 360 can be seen with the artificialpupil. According to some embodiments, the artificial pupil need not benecessarily black and may be another suitable color, based oncompatibility with third party iris recognition software.

The pupil boundaries, for example, 304, 326 and 356 and the irisboundaries (iris/sclera boundary areas), for example, 306, 328 and 358are calculated using a Hough transform, according to one embodiment. Thepupil segmentation module 206 and the iris segmentation module 208employ edge detection using the edge detection module 209 to generateedge maps which works for varying scales of grayscale pupils, even ininstances with low edge contrast. Once the pupil segmentation module 206determines the segmented pupil area (and therefore, the pupil contour)and the pupil and iris have been warped to form circular regions, thesegmented pupil area is replaced with a black or dark disk to simulatethe appearance of a dark pupil.

FIG. 4A depicts a flow diagram for a method 400 for edge detection inaccordance with one embodiment of the present invention. The method 400is an exemplary illustration of the operation of the edge detectionmodule 209 used to detect pupil and iris boundaries.

The method begins at step 402 and proceeds to step 404. At step 404, anedge map is generated from an image of an eye, for example, input image101. An exemplary edge map for an iris image which was brightlyilluminated is shown in FIG. 48, image 420. Image 422 is an edge map foran iris image which was not as brightly illuminated, i.e., an indistinctpupil whose edges are not as clearly visible as those in image 420.

At step 406, candidate pupil contours are constructed for the given edgemap. Step 406 consists of sub-steps 406A and 4068. At sub-step 406A, afirst candidate pupil contour is created from a best fitting circle, asshown in FIG. 48, image 420. For example, a Hough transform or RANSAC(random sample consensus) method can be used to find the circle that hasthe greatest level of support in the edge map in the sense that thelargest fraction of circle points for that circle coincide with edgepoints. At step 4068, a second candidate pupil contour is constructedfrom a best inscribed circle as shown in FIG. 48, image 422. Those ofordinary skill in the art would recognize that an inscribed circle is acircle that can be drawn in an area/region of the edge map so that noedge points (or no more than a specified small number of edge points)lie within the circle. According to one embodiment, the best inscribedcircle is the largest such inscribed circle that can be found in thearea/region of the pupil. Then method then proceeds to step 408, wherethe method 400 determines the best matching candidate pupil contour fromthe first and second candidate pupil matching contours for the edge map.According to one embodiment, the best match is determined by assessing alevel of support for the best fitting circle and selecting the bestfitting circle as the best match if this level of support is above athreshold value. The best inscribed circle is selected as the best matchif the level of support for the best fitting circle is below a thresholdvalue.

According to one embodiment, an automatic process based on how well thebest fit contour (circle) matches the edge contour in the edge contourmap is used to decide which candidate contour to choose. For example,for the best supported circle described above, a subset of edge pointscan be selected that is limited to those edge points whose angularorientation is consistent with that edge point being a part of thecandidate circle. In other words only edge points whose direction isapproximately perpendicular to the direction from the estimated centerof the candidate circle are included. This process eliminates fromconsideration those edge points that may accidentally fall at thecorrect position to be part of the circle but that do not correspond tothe actual circle contour. If the proportion of such selected edgepoints is greater than some specified fraction (e.g. 20%) of the numberof points comprising the circle then the level of support for thatcircle is deemed to be sufficient and the best fitting circle isselected. If the level of support by the selected edge points is lessthan this threshold then the best fitting circle is deemed to haveinsufficient support and the best inscribed circle is selected instead.Generally speaking, the best fit candidate contour will provide accuratepupil segmentation in the bright pupil image, as shown in FIG. 48, image420, where the bright colored eye edge map is overlayed with thebest-inscribed circle 430 and the best fitting circle 432. The methodthen terminates at step 412 when a best matching candidate pupil contouris found.

In some instances, iris images may be captured over a range of obliqueviewing conditions, for example, where gaze deviation with nasal gazeangles ranges from 0 to 40 degrees, as shown in FIG. 3D. The tiltcorrection module 210 rectifies the images for this tilt and generates atilt corrected image. According to one embodiment, a tilt-correctedimage may be generated by estimating or determining the magnitude anddirection/angle of tilt, and then applying a geometric transformation tothe iris image to compensate for the oblique viewing angle. In the casewhere the iris is a flat disk, the simplest form of this transformationis a stretching of the image in the direction of the tilt to compensatefor the foreshortening caused by the angle between the iris and theimage plane. Such a non-isotropic stretching is mathematicallyrepresented as an affine transformation. A more accurate version of thisgeometric de-tilting replaces the affine transformation with aprojective transformation which better represents the imagerepresentation of a pattern on a flat, tilted surface.

The correction module 204 has several uses independent of the othercomponents of the iris processor 100. For example, the correction module204 may be used to detect a person's gaze, or to track a person's gazecontinuously by capturing one or more frames of a person's eyes. Thetilt correction module 210 may, for example, be used to continuouslytrack a user's gaze on a mobile device and scroll a document, perform aswipe or the like. This tilt detection can be used, for example,independently of the matching processor 106 described in FIG. 1 toenable or disable the display of a mobile device.

In some embodiments, the correction module 204 corrects the input image101 prior to the segmentation module establishing artificial pupil discson the input image 101. In some instances, tilt correction may stillshow distortions such as the apparent eccentric pupil compression of thenasal portion of the iris, causing difficulty in biometrically matchingthe iris with a stored iris image. The distortion is caused by theoptical effect of the cornea and anterior chamber of the human eyethrough which the iris is imaged. These two structures have similarrefractive indexes (1.336 for the aqueous humor that fills the anteriorchamber and 1.376 for the cornea) so that together their optical effectis approximately that of a single water-filled plano-convex lens incontact with the iris. Viewed from an oblique angle such a lens willproduce asymmetric distortion in the iris image, compressing the imagein some areas and expanding it in others. The tilt corrected imagegenerated by the tilt correction module 210 is coupled to the cornealcorrection module 212, which corrects for the above described cornealdistortion.

FIG. 4C depicts a flow diagram for a method 440 for corneal distortioncorrection in accordance with exemplary embodiments of the presentinvention. The method 400 is an exemplary illustration of the operationof the edge detection module 209. The method begins at step 402 andproceeds to step 404. At step 404, the tilt correction module 210estimates the angle of tilt of the iris with respect to the cameraorientation. The tilt can be estimated roughly by finding the pupilcenter and measuring the distance between that center and the brightreflection in the cornea caused by the near infra-red illuminator usedin iris imaging. Other methods of tilt estimation known to those ofordinary skill in the art may also be used. Indeed, any method of tiltestimation may be substituted herein.

The method proceeds to step 406, where the image is corrected for theperspective distortion, i.e., the foreshortening of the iris thatoccurs. The effect of foreshortening can be approximated as a simplecompression of the captured image in the direction or tilt. This effectcan therefore be compensated for by simply stretching the image in thedirection derived from the tilt estimation step. A more accuratecorrection can also be performed by using a projective transformation tomore precisely capture the foreshortening effect.

Finally, at step 448, the method 400 corrects for effects of opticaldistortion due to viewing through the tilted cornea. According to oneembodiment, approximate correction for the optical distortion discussedabove can be achieved by measuring and correcting the effects of pupileccentricity and pupil elongation. The method terminates at step 450.

As seen in image 460 in FIG. 4D, after foreshortening correction basedon tilt estimation, the pupil still appears shifted to the left withrespect to the center of the iris and the pupil appears elongated in thehorizontal direction. These effects are caused by the optical effects ofthe cornea. The corneal correction module 212 corrects for thesedistortions without modeling the optical elements that produced them bynon-linearly warping the iris area/region to force the iris contour 466and pupil contour 468 to become concentric circles. The cornealcorrection module 212 creates this nonlinear warping function bydefining a set of spokes 470 that connect points on the non-circularpupil contour 468 to corresponding points on the non-circulariris/sclera contour 466 and mapping each spoke of the spokes 470 to aposition connecting a synthetic circular pupil contour 472 to aconcentric circular iris/sclera contour 474. The describedtransformation is then applied to the underlying image 460. The resultof this mapping (with appropriate interpolation) is shown in image 476.After the pupil and iris areas/regions have been shifted to be inconcentric circles, the coding process can be more accurately performedwith better matching results.

After such a corrected image is constructed as described above, iriscoding and matching can be performed using any desired iris biometricalgorithm designed to be applied to iris images captured under standardcontrolled conditions. For example, the classic method of Daugman(Daugman, J., “High confidence visual recognition of persons by a testof statistical independence”, IEEE Transactions on Pattern Analysis andMachine Intelligence, 15 (11), pp 1148-1161 (1993)) can be applied.However, methods developed by others can also be used, including but notlimited to those of Munro (D. M. Monro and D. Zhang, An Effective HumanIris Code with Low Complexity, Proc. IEEE International Conference onImage Processing, vol. 3, pp. 277-280, September 2005) and Tan (Tan etal, Efficient Iris Recognition by Characterizing Key Local VariationsIEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 13, NO. 6, June 2004).

FIG. 5 depicts a block diagram of a coding processor 500 in accordancewith exemplary embodiments of the present invention. The codingprocessor 500 comprises a coordinate module 502 and an extraction module506. The coordinate module 502 constructs an invariant coordinate systemfor an invariant coordinate system image representation that allows irisinformation extracted from varying iris images to be brought intoregister, so that corresponding spatial information can be compared. Theextraction module 506 extracts information from the iris image forsupporting a strong rejection of the hypothesis that two eye imagespresented represent statistically independent patterns. The codingprocessor 500 prepares the segmented and corrected iris image 220 foraccurate matching with other iris images and allows unconstrained iriscapture applications. For example, image size and focus may vary withdistance, in addition to individual iris structure variations andvariation with illumination wavelength of spatial information content ofan iris structure. Generally, iris coding is based on angularfrequencies between about 15 and 40 cycles/2 pi or 2.5 and 6 pixels percycle, where according to one embodiment, the present applicationachieves robust matching based on the codes generated by the codingprocessor 500 down to approximately 40 pixels per iris diameter.

According to one embodiment, the coding processor 500 uses a variant ofDaugman's local phase representation, which encompasses amulti-resolution coding approach rather than choosing a single scale ofanalysis. Lower frequency components remain available in lowerresolution images and are less prone to loss in defocused or otherwisedegraded images. In one embodiment, the variant of Daugman's local phaserepresentation allows for dense coding that is useful when dealing withiris images in which significant occlusion may occur. Although therobust segmentation and rectification process described above generatescorrected iris images that can be used with a variety of iris coding andmatching algorithms, there are advantages in some situations toretaining properties of standard algorithms. One advantage of theDaugman type phase coding approach is that it generates a code thatrepresents all available parts of the iris images. This is in contrastto an approach that uses sparse local features that might be occluded orotherwise unavailable in a particular image to be matches. Further, theuse of multiresolution phase approach preserves the possibility ofachieving code-level compatibility with existing phase-basedrepresentations. In addition to containing multi-scale information, thecode that is created can incorporate additional information tofacilitate estimation of iris code alignment and spatial interpolationof local structure information prior to comparison.

As shown in FIG. 5, the coding processor 500 comprises the coordinatemodule 502. The coordinate module 502 transforms the rectified irisimage 220 into a polar iris image 504. In this polar iris image 504 thepupil boundary appears at the top (notice the specular reflection of abiometric scanner illuminator column) and the iris-sclera boundary areaappears at the bottom. The angular dimension runs clockwise from 3o'clock at the left of the image. Proceeding from left to right, thelower and upper eyelids can be seen. Note that in image 504 theeyelashes extend from the upper eyelid all the way into the pupil.

Subsequently, after converting the rectified iris image into a polarcoordinate image, the image 504 is coupled to the extraction module 506that filters and subsamples the polar iris image 504 to produce amulti-resolution iris code representation 520, an example of which isshown in FIG. 6. According to an exemplary embodiment, the image 504 ispassed through a series of bandpass filters to produce a set of filteredimages. FIG. 6 shows an example of a polar iris image 620, beingfiltered by filters 121 (Filters 1 . . . 5) and producing an iris code622 comprising filtered bands 600, 602, 604, 606 and 608, respectivelyhigh-frequency domain bands to low frequency domain bands. The fivebands shown correspond to Gabor filter (a linear filter used forharmonic analysis, wavelet decompositions, and edge detection) carrierwavelengths of 6, 8, 12, 16, and 24 pixels with respect to a polar imagesampled at 200 pixels around the iris. Therefore, the frequenciescorrespond approximately to angular spatial frequencies of 33, 25, 16,12, and 8 cycles per 2 pi.

The higher frequencies are comparable to those used in standard irismatching algorithms. The mask 610 is the union of two masks: a mask(common to all bands) based on analysis of the intensities in the inputpolar iris image 504 that masks off area corresponding to specularreflections and approximate location of eyelid and eyelash areas, and amask based on the signal strength in the Gabor filtered image that masksoff areas in which local phase measurement is unstable (unstableregions). Multi-resolution representation as shown in iris code 622allow representation of information from images at differentcamera-subject distances that result in iris images differing in numberof pixels per unit distance at the iris as well as oblique camera viewscausing foreshortening and optical demagnification, as discussed abovewith reference to FIGS. 2-4D.

Other properties of an iris code representation 520 include a completedescription of the filter characteristics, spatial sampling,representation and quantization. Filter characteristics comprise one ormore of center frequencies, bandwidths, functional type (e.g. logGabor), and orientation tuning. Spatial sampling comprises one or moreof spacing along the radial and angular normalized image axes for eachfilter type, and quantization specifies the number levels with whicheach value is represented or number of bits assigned to each. Accordingto exemplary embodiments, the iris code representation 520 and exemplaryiris code 622 is a warpable code allowing for interpolation by usingsub-Nyquist spatial sampling requirements for each filter 1 . . . 5 infilters 621 that produces provide a criterion for sufficient samplingfor accurate interpolation. The sub-Nyquist spatial sampling is combinedwith a finer intensity quantization than the 1 bit per complex phasecomponent used in Daugman-type coding. For example, if 4 bits are usedfor each complex phase component this corresponds to roughly 64 steps inphase angle and thus a maximum interpolation error of pi/32 radians orless than six degrees.

In some embodiments, non-quantized iris codes may also be matched, whereoriginal complex band-pass filter outputs are stored withoutquantization. In one embodiment, the filter outputs are normalized inmagnitude so that each represents a complex number on the unit circle.Data masks are generated based on occlusions and local complexamplitude. The match measure that is the closest analog of the standardHamming distance measure of a Daugman iris code is based on a phasedifference histogram. This histogram constructed by computing the anglesbetween the phase vectors of the two codes being compared (see FIG. 6),and compiling a histogram (subject to the valid data mask) of phasedifferences between −pi and pi. These phase differences should be smallif the codes represent the same eye and more or less uniformlydistributed if the codes represent statistically independent eyes.

An example of two such histograms is shown in FIG. 7. The histogram onthe left corresponds to an impostor match and the one on the right to anauthentic match. As expected, the authentic distribution is tightlyconcentrated around a zero phase shift with only a small proportion ofthe phase difference values larger than pi/2 in absolute value. Incontrast, the impostor histogram shows many large phase differences andno clear evidence of concentration around zero value. The fraction ofvalues larger than pi/2 can be used to generate a match statistic thatbehaves very much like Daugman code Hamming distance if this is desired.However, there are many other measures of central concentration anddispersion that may be used to distinguish between authentic andimpostor distributions, as will be described below. Furthermore, givesufficient training sets of impostor and authentic histograms it may bebeneficial to use statistical classification or machine learningtechniques such as discriminant analysis, Support Vector Machines,Neural Networks, or Logistic Regression to construct an optimal decisionprocedure for some class of data.

Measurements of the central value of a phase difference histogram, andof the dispersion around that point takes into account the fact that thephase differences are angles and therefore the histogram is distributedon a closed circle. Ordinary mean and variance measures (or highermoments if necessary) do not correctly represent the desired propertiesfor angular data. The Von Mises distribution provides a wellcharacterized method for estimating properties of data distributed overa periodic domain. The Von Mises mean gives an estimate of the center ofconcentration of the distribution and the concentration parameter andestimate of the spread. Both quantities can be computed easily if thephase differences are represented as unit complex numbers. In this case,the mean estimate is simply the angle corresponding to the sample meanof the complex numbers, and the concentration parameter is simplyrelated to the complex magnitude of the sample mean.

According to another embodiment, data is analyzed over a periodic domainby employing a Fourier series expansion to compute circular harmonics.Like the Von Mises parameters, the relative magnitude low order circularharmonics give information about degree of concentration of the data.Transformation of the histogram data using circular harmonics isbeneficial prior to use of learning techniques to construct a decisionprocedure.

The phase difference histogram aids in analysis of the match levelbetween two codes but does not represent all of the information relevantto the comparison of two codes. If the phase difference value varies asa function of the absolute phase then the histogram shows lowconcentration (i.e. large dispersion) even given a strong relationship.According to one embodiment, a Mutual Information or other conditionalentropy description is employed to prevent this problem, which measuresthe reduction in the entropy of one random variable given knowledge ofthe value of another random variable. This more completecharacterization can detect relatedness even where the variables areuncorrelated.

Another limitation of the phase difference histogram is that itcompletely suppresses spatial information since the histogram is aglobal statistic. However, local or patchwise uniformity of phasedifferences or other detectable relatedness would also be sufficient toconclude that the codes are not independent. This local analysis couldbe achieved using local histogram analysis, mutual information, orspatial correlation analyses.

FIG. 7 depicts a block diagram of a matching processor 700 in accordancewith exemplary embodiments of the present invention. The matchingprocessor 106 comprises an alignment module 702 and a flow estimationmodule 704. According to exemplary embodiments, the iris code 520generated by the coding processor 500 as shown in FIG. 5 is coupled tothe alignment module 702. The alignment module 702 performs variousalignments to the iris code 520 based on matching algorithms describedbelow. The alignment module 702 further couples the iris code 520 to theflow estimation module 704 to generate estimated flow vectors to aid inmatching. The alignment module 702 compares the iris code 520 to an iriscode 706 from database 708 to determine whether a match exists. If amatch does not exist, more iris codes from the database 708 are comparedwith the iris code 520. Match scores are determined, and if the matchscore meets or is below a predetermined threshold, then a match exists.According to exemplary embodiments, a Hamming distance is used as amatch score. Ultimately, the matched iris data 108 is returned by thematching processor 700. According to some other embodiments, flowestimation is applied to information derived from the unknown iris code520 and the stored iris code 706. This information may be part of theiris code 520 per se or it may not. The resulting flow field from theflow estimation module 704 is used to generate a modified iris code thatis matched against a reference iris code by the matching processor 700to produce a match score 720.

In a binary context, i.e., comparing iris codes, a Hamming distancerepresents a binary distance based on XOR operations to computes thenumber of bits that differ between two binary images. According toexemplary embodiments, the alignment module 702 performs a Daugmanbarrel shift on the iris codes, i.e., finds the iris code rotation thatprovides the best match between the iris codes being compared. In oneembodiment, the matching algorithm employed by the matching processor700 is a modified algorithm using the Hamming distance (HD) for each setof barrel shift positions and taking the lowest Hamming distance as thescore for that pair of codes. If the score is below some threshold (thatmay be adjusted based on the estimated number of statistical degrees offreedom represented by the codes) then the unknown code is deemed to bea match. If the HD is above the threshold then the unknown code islabeled an impostor. In one embodiment, the threshold depends on detailsof the iris code structure and on the statistical requirements of thematching scenario.

The modified algorithm employed by the alignment module 702 barrelshifts the iris codes being compared and also locally aligns the iriscodes to each other to compensate for inaccuracies in iris imagenormalization due to uncorrected optical distortion or complexities ofiris dilation and contraction. The local alignment function, performedby alignment module 702, allows compensation for distortions in theinput iris image that are not uniform across the iris. This isaccomplished by shifting local regions of the code to bring them intomore accurate alignment with corresponding regions of the referencecode. However, if this process is performed using very small estimationregions, virtually any iris code can be made to match any other iriscode, which can result in false matches being generated. This falsematching problem can be avoided by imposing suitable smoothnessconditions on the estimated flow field. For example, if the flow fieldis estimated by performing local translation estimation using relativelylarge estimation regions then the local flow estimates will representthe average motion over this relatively large region.

If such region overlaps, so that the regions used to compute the flowvectors for neighboring locations contain much of the same content, thenthe displacement estimates will change gradually with position and falsematching will be prevented. Alternatively, local displacement estimatesmade with small estimation regions can be smoothed by spatial filteringto eliminate rapid changes in local displacement. As a furtheralternative, a global parametric representation such as a low orderpolynomial or truncated Fourier series can be used, and the parametersof this parametric representation estimated directly or fit to localestimates. Such parametric representation has inherent smoothnessproperties that prevent too rapid change in local shifts to occur. Thealignment module 702 further produces multiple match scores for eachcomparison, between iris code 520 and 706 for example, because each iriscode contains multiple frequency bands.

FIG. 8 depicts the process of matching iris codes performed by thematching processor 700 in accordance with exemplary embodiments of thepresent invention. As in standard iris code matching, the first code 800and the second code 802 to be matched are represented as values over therectified (e.g., polarized) iris image coordinate system consisting ofan angular and a normalized radial coordinate. A local displacementfunction or flow field is computed by the flow estimation module 704 ofthe matching apparatus in FIG. 7 and coupled to the alignment module 702that best aligns structure in the first iris code 800 to correspondingstructure in the second code 802, subject to some smoothness orparametric constraint. This flow field estimation can include the effectof standard barrel shift alignment or that can be performed as aseparate step. The vectors in this flow field each specify thedisplacement in the normalized image coordinate system at which theimage structure in the first code 800 best matches the structure in thesecond code 802.

Each band in first iris code 800 is transformed using this displacementfunction to produce an aligned iris code, and the Hamming distancebetween this aligned iris code and the corresponding band of the secondcode 802 is computed. Because the transformation is constrained to besmooth, impostor codes will not be transformed into authentic codes aswill be described below.

The flow estimation module 704 computes a flow field at a reducedresolution for each iris code, and smoothly interpolates the flow fieldto produce a final estimate. According to an exemplary embodiment, theflow estimation module 704 employs a pyramid-based coarse-fine flowestimation technique, though those of ordinary skill would recognizethat other techniques may be used instead. The alignment module 702introduces a small local shift in one band of each of the first iriscode 800 and the second iris code 802, the shift being in the angulardirection and equal at all radial positions. The displacement shift alsovaries smoothly in the angular direction. Calculating a Hamming distanceat this point would result in a non-match (e.g., if a Daugman-typematching algorithm is employed a Hamming distance greater than 0.33indicates a non-match). A coarse-fine algorithm is used by the flowestimate module 704 to estimate the flow field between codes 800 and 802from the low resolution bands of the codes.

The alignment module 702 then warps the code 800 by the estimated flowfield resulting in a significantly decreased Hamming distance, signalinga high confidence match. For a Daugman-type matcher, a Hamming distance<0.3 indicates a high confidence match. Various matches may correspondwith different Hamming distance values qualifying as high confidencematches. According to another embodiment, the matching processor 700 maymatch two iris codes by employing a mutual information measure based onthe phase angles of the codes being compared as well as measures basedon the local difference of phase angles.

FIG. 9 is a depiction of the coarse-fine algorithm described above toestimate flow-field of an iris code in accordance with exemplaryembodiments of the present invention. Coarse-fine refinement operates ona “pyramid” structure that is essentially a collection of bandpassfiltered version 904-1 to 904-N and 906-1 to 906-1 of the input images900 and 902 respectively, as shown in FIG. 9.

Starting with the lowest frequency bands 904-1 and 906-1, at each levelin the pyramid the displacements 908-1 to 908-N estimated at theprevious level are used to warp the current level image and then anincremental displacement is computed based on the residual differencebetween the warped level and the corresponding pyramid level in theother image. This process continues until the highest level is reachedand the result is the final estimated flow field 910.

Since the multi-resolution iris code is itself a collection of bandpassfiltered versions of the images with which alignment is desired,according to one embodiment, these bands themselves could be used todrive the alignment process in the alignment module 702. This wouldproduce a truly “self aligning” iris code. In this approach there is noneed to store additional alignment data as part of the multi-resolutioniris code structure.

FIG. 10 is a flow diagram depicting method 1000 for estimating flowfield between two iris codes in accordance with exemplary embodiments ofthe present invention. The method is an implementation of the flowestimation module 704. The method begins at step 1002 and proceeds tostep 1004.

At step 1004, the flow estimation module 704 generates a first pluralityof images from a first input image (i.e., a first iris code) and asecond plurality of images from a second input image (i.e., a secondiris code to be matched against) using a bandpass filter, the first andsecond plurality of images comprising images ranging from low frequencyto high frequency bands.

The method subsequently proceeds to step 1006, where the flow estimationmodule 704 selects an image from the first plurality of images in thelowest frequency band that has not been processed, i.e., for which thereis no previous flow-field estimate. At step 1008, the flow estimationmodule 704 determines whether a flow field has been estimated in a lowerfrequency band between the first and second plurality of images. If aflow field has been estimated in a lower frequency band, the methodproceeds to step 1010, where the selected image is warped using thelower frequency band flow field estimate. If a flow field estimate in alower frequency band has not been estimated, then the method proceeds tostep 1012, where a flow field is estimated by the flow estimation module704 on the residual difference between the warped image and a secondimage at the same frequency band from the second plurality of images.

The method then proceeds to step 1014, where the flow estimation module704 determines whether all frequency bands have been processed. If not,then the method returns to step 1006 to process the next higherfrequency band until all frequency bands have been processed. When allfrequency bands have been processed (i.e., warped by lower frequencyflow field estimates), the method proceeds to step 1016, where the finalflow field estimate is returned to the matching processor 700. Themethod terminates at step 1018.

FIG. 11 is a flow diagram depicting method 1100 for estimating flowfield between two iris codes in accordance with exemplary embodiments ofthe present invention. The method is an implementation of the irisprocessor 100. The method begins at step 1102 and proceeds to step 1104.

At step 1104, the pre-processor 102 pre-processes and input imagecontaining an eye to produce a rectified iris image with rectified pupiland iris boundaries, and correction for tilt and corneal distortion.

The method proceeds to step 1106, where the coding processor 104 codesthe rectified iris image into a multiresolution iris code. The iris codecontains multiple frequency band representations of a polarized versionof the rectified iris image. The method then proceeds to step 1108,where the multiresolution iris code is compared to a set of stored iriscodes in a database to determine whether the iris code is contained inthe database and returns data associated with the matched iris. Themethod terminates at step 1110.

FIG. 12 depicts a computer system for implementing the iris processor100 in accordance with exemplary embodiments of the present invention.The computer system 1200 includes a processor 1202, various supportcircuits 1205, and memory 1204. The computer system 1200 may include oneor more microprocessors known in the art similar to processor 1202. Thesupport circuits 1205 for the processor 1202 include conventional cache,power supplies, clock circuits, data registers, 1/0 interface 1207, andthe like. The 1/0 interface 1207 may be directly coupled to the memory1204 or coupled through the support circuits 1205. The 1/0 interface1207 may also be configured for communication with input devices and/oroutput devices such as network devices, various storage devices, mouse,keyboard, display, video and audio sensors, visible and infrared camerasand the like.

The memory 1204, or computer readable medium, stores non-transientprocessor-executable instructions and/or data that may be executed byand/or used by the processor 1202. These processor-executableinstructions may comprise firmware, software, and the like, or somecombination thereof. Modules having processor-executable instructionsthat are stored in the memory 1204 comprise an iris processor 1206. Theiris processor 1206 further comprises a pre-processing module 1208, acoding module 1210 and a matching module 1212. The memory 1204 mayfurther comprise a database 1214, though the database 1214 need not bein the same physical memory 1204 as the iris processor 1206. Thedatabase 1214 may be remotely accessed by the iris processor 1206 via acloud service. Additionally, the iris processor 1206 may also haveseveral components that may not be co-located on memory 1204. Forexample, in some embodiments, the pre-processing module 1208 is local tothe computer system 1200, while the coding module 1210 and the matchingmodule 1212 may be accessed as cloud services via a wired or wirelessnetwork. In other instances, only the matching module 1212 is accessedvia a network. Communication between each module may be encrypted as thedata travels over the network.

The computer system 1200 may be programmed with one or more operatingsystems 1220 (generally referred to as operating system (OS)), that mayinclude OS/2, Java Virtual Machine, Linux, SOLARIS, UNIX, HPUX, AIX,WINDOWS, WINDOWS95, WINDOWS98, WINDOWS NT, AND WINDOWS2000, WINDOWS ME,WINDOWS XP, WINDOWS SERVER, WINDOWS 8, Mac OS X, IOS, ANDROID amongother known platforms. At least a portion of the operating system may bedisposed in the memory 1204.

The memory 1204 may include one or more of the following random accessmemory, read only memory, magneto-resistive read/write memory, opticalread/write memory, cache memory, magnetic read/write memory, and thelike, as well as signal-bearing media as described below.

The computer system 1200 may be a mobile device such as a cellular phoneor tablet device, for example. The mobile device may contain a cameraand have the iris processor 1206 stored on memory as an application. Insome embodiments, the iris processor 1206 may be a part of the operatingsystem 1220. In some instances, the iris processor 1206 may be anindependent processor, or stored on a different chip than the processor1202. For example, often mobile devices have camera processing modulesand the iris processor 1206, or portions of the iris processor 1206, mayreside on the camera processing module, where the imager in the camerais a CCD or CMOS imager. In some instances, the mobile device may becustomized to include some sensors, the type of the camera imager, orthe like.

FIG. 13 illustrates the iris processor 100 in an exemplary operatingscenario. In this case a combination of face tracking and asteerable/autofocus iris capture device comprising the iris processor100 is used to identify multiple individuals walking down a corridor.The capture device may be placed unobtrusively, e.g., at the side of thecorridor, and can operate at a large range of capture distances yieldinga range of presentation angles, if a device with the capabilitiesdisclosed herein is used. By combining identity information derived fromiris biometrics with tracking information from the person trackingsystem it is possible to associate an identity (or failure to identifyan identity) with each person passing through the active capture region.

Referring now to FIG. 14, an embodiment of an iris biometricrecognition-enabled access control assembly 1412 is installed in anaccess control structure 1416 of a physical facility 1400. Theillustrative access control assembly 1412 is embodied as a door lockassembly in which the access control structure 1416 is a door. The door1416 may be embodied as any type of door that provides a barrier toingress and egress with respect to the facility 1400, such as a hinged,sliding, or revolving door. In other embodiments, the access controlstructure 1416 may be embodied as, for example, a lid for a containerthat is secured by the access control assembly 1412 or a drawer orcompartment that is secured by the access control assembly 1412.Operation of the access control structure 1416 (e.g., opening andclosing) may be performed manually or in an automated fashion (e.g.,pneumatically or electronically controlled). The illustrative facility1400 is embodied as a building or a room within a building. In otherembodiments, however, the facility 1400 is embodied as a vehicle, acabinet, a storage container (such as a safe or a safe deposit box), orany other structure in which people or things may be at leasttemporarily retained. The door 1416 is supported by a support structure1418. The illustrative support structure 1418 is a wall of the facility1400; in other embodiments, the support structure 1418 may be a part ofthe frame or chassis of an automobile (in the case of car doors), or thebody of a container, drawer, or cabinet, for example.

The illustrative door lock assembly 1412 includes, integral therewith,an iris biometric recognition module 1414. Although not required forpurposes of the present disclosure, the door lock assembly 1412 alsoincludes a handle 1410. Further details of an embodiment of the doorlock assembly 1412 and the iris biometric recognition module 1414 areshown in FIGS. 15-17, described below. In operation, the biometricrecognition module 1414 detects the presence of a human subject 1424 ina capture zone 1420. The capture zone 1420 includes a physical area(e.g., a three-dimensional area) that is located at a distance D1 awayfrom the biometric recognition module 1414 and which is a width W1 wideand a vertical height H1 high. The dimensions D1, W1, H1 of the capturezone 1420 can be defined at least in part by the selection of thecomponents for the biometric recognition module 1414. For example, useof a stronger power supply to power the biometric recognition module1414 can increase the distance D1 and vice versa. Alternatively or inaddition, use of a different type of imaging device, lightingarrangement, or optics can vary the dimensions of the capture zone 1420.For instance, selection of an imaging device with a wide field of viewcan increase the size of the capture zone 1420 and vice versa. In someembodiments, the distance D1 is in the range of at least about 45-75centimeters relative to the location of the biometric recognition module1414. In other embodiments, the distance D1 is less than or equal to 45centimeters, and in still other embodiments, the distance D1 is greaterthan or equal to 75 centimeters, relative to the location of thebiometric recognition module 1414. In some embodiments, the width W1 isin the range of at least about 2 feet to about 4 feet wide relative tothe location of the biometric recognition module 1414 (e.g., about 1 toabout 2 feet on either side of the biometric recognition module 1414).In other embodiments, the width W1 is greater than or equal to 4 feet,and in still other embodiments, the width W1 is less than or equal to 2feet.

The capture zone 1420 also includes an area that is located at avertical height H1 above a ground plane 1422 (e.g., a floor). In someembodiments, the vertical height H1 is in the range of at least about 3feet to about 7 feet above the ground plane 1422 (e.g., the range of H1includes a typical range of heights of human subjects, from children toadults). In other embodiments, the vertical height H1 is less than orequal to 3 feet relative to the ground plane 1422. In still otherembodiments, the vertical height H1 is greater than or equal to 7 feetrelative to the ground plane 1422.

In operation, and as described in more detail below, the iris biometricrecognition module 1414 obtains an image of the face and eyes of thehuman subject 1424 using an imaging device (e.g., one or more digitalcameras). Based on one or more characteristics of the image of the faceand eyes (e.g., pixel size, or the number of pixels making up thedepiction of the face or eyes relative to the entire image), the irisbiometric recognition module 1414 is able to estimate the distance D1(which is, in operation, the linear distance from the iris biometricrecognition module 1414 to the face, eye, or iris of the human subject1424) and focus the imaging device on a narrower field of view capturezone 1426, which includes at least one of the subject 1424's irises. Theiris biometric recognition module 1414 captures one or more images ofthe subject 1424's iris, processes the captured iris image(s) using,e.g., the iris processing techniques described above, and performs amatching operation using, e.g., the iris matching techniques describedabove, in order to evaluate, e.g., the identity or security credentials,of the human subject 1424. The iris biometric recognition module 1414outputs an electrical signal indicative of the results of the irismatching operation (e.g., an indication of whether the human subject1424 has been positively identified or has the requisite securitycredentials). The access control assembly (e.g., door lock assembly)1412 uses the iris match determination information output by the irisbiometric recognition module 1414 to determine whether to lock or unlockthe access control device (e.g., door) 1416. In other embodiments, theiris matching operations and match determinations are done off themodule 1414 (e.g., on a server computer in “the cloud”). In thoseembodiments, iris match determinations are communicated by theoff-module device performing the match operations (e.g., a server) backto the module 1414 and/or to another device (e.g., a door lockassembly).

Referring now to FIG. 15, a door lock assembly embodiment 1500 of theaccess control assembly 1412 is shown in greater detail, in an explodedview, in connection with a cut away portion 1526 of the access controlstructure (e.g., door) 1416. The door lock assembly 1500 includes aninner assembly 1552 and an outer assembly 1510, each of which areinstalled on opposite sides of the access control structure 1526. Anembodiment 1514 of the iris biometric recognition module 1414 issupported by the outer assembly 1510. Components of the iris biometricrecognition module 1514 are shown in more detail in FIGS. 16-17,described below. The iris biometric recognition module 1514 is securedto the outer assembly 1510 by a gasket 1516 and associated fasteners(e.g., screws or bolts, not shown). The illustrative gasket 1516provides a weatherproof seal to allow use of the iris biometricrecognition module 1514 in all types of environments (e.g., variousweather conditions, lighting conditions, etc.).

The outer assembly 1510 includes a handle 1512, which is pivotablymounted to a top surface of the outer assembly 1510. The illustrativehandle 1512 is a pivot-style handle, but any suitable type of handle maybe used, including push handles, knobs, and/or others. While notrequired for purposes of the present disclosure, the illustrative outerassembly 1510 also includes a keypad 1524 by which a person can input,e.g., a personal identification number (PIN) for identity verificationand/or access authorization purposes. A cover window 1518 is attached tothe outer assembly 1510 and fits over the iris biometric recognitionmodule 1514 after installation. The window 1518, or at least the portionof the window 1518 that covers the iris biometric recognition module1514, is constructed of a plastic material that is transparent at leastto electromagnetic radiation in the infrared spectrum (e.g.,electromagnetic radiation having a wavelength just greater than that ofthe red end of the visible light spectrum but less than that ofmicrowaves, in the range of about 700 nm to about 1 micron). Forinstance, the window 1518 may be constructed with a thermoplasticpolycarbonate material such as a TEXAN brand polycarbonate sheet.

The outer assembly 1510 and the inner assembly 1552 are each coupled toand supported by the access control structure 1526 (e.g., by screws orother fasteners, a snap fit mechanism, etc.). Apertures or windows 1542,1544, 1546 are formed in the gasket 1516, the outer assembly 1510, andthe access control structure 1526, respectively, and are aligned withone another so that an electrical connector (e.g., an electrical cable)1522 of the iris biometric recognition module 1514 can pass through theapertures 1542, 1544, 1546 and connect with a door lock assemblycontroller board 1540. Thus, electrical output signals generated by theiris biometric recognition module 1514 (e.g., iris match determinationdata signals) can be transmitted from the iris biometric recognitionmodule 1514 to the door lock assembly controller board 1540 via theelectrical connector 1522. After installation, the iris biometricrecognition module 1514 is disposed within the space created by theapertures 1542, 1544, 1546. In some embodiments, the iris biometricrecognition module 1514 is removably coupled to the door lock assembly1500 (e.g., retained by a latch or detent mechanism, or other suitablefastener). In other embodiments, the iris biometric recognition module1514 may be fixedly secured to the door lock assembly 1500 so as to benon-removable or removable with non-trivial human effort or by the useof tooling.

The access control structure 1526 also includes, defined therein,apertures 1548, 1550. The handle 1512 couples with a latch shaft 1534 ofa dead bolt/latch assembly 1520 through the aperture 1548 in the accesscontrol structure 1526. A door latch/dead bolt assembly 1531 is disposedin the aperture 1550. The door latch/dead bolt assembly 1531 includes adead bolt 1532 and a latch 1530. Each of the dead bolt 1532 and thelatch 1530 are movable between locked and unlocked positions. An innerhandle 1513 (located on the opposite side of the inner assembly 1552from the handle 1512, after installation) is also coupled to the innerassembly 1552 and to the latch shaft 1534. The latch 1530 is manuallyactivated, e.g., by either the handle 1512 or the handle 1513 drivingthe latch shaft 1534 through an aperture 1523 in the body of the doorlatch/dead bolt assembly 1531, causing the latch 1530 to move from anunlocked position to a locked position (or vice versa).

A dead bolt drive shaft 1533 is operated by a motor 1536, which iselectrically connected to the door lock controller board 1540 (e.g., byinsulated wiring, not shown). A power supply compartment 1537 isconfigured to house a power supply 1538 (e.g., one or more batteries,such as commercially available NiCad, “AA” or “AAA” batteries). Thepower supply 1538 may be removable or non-removable in differentembodiments of the door lock assembly 1500.

The dead bolt 1532 is activated by the motor 1536 driving the dead boltdrive shaft 1533 through an aperture 1521 in the body of the deadbolt/latch assembly 1531, thereby causing the dead bolt 1532 to movefrom an unlocked position to a locked position (or vice versa). Due tothe electrical communication link (by, e.g., the connector 1522) betweenthe iris biometric recognition module 1514 and the door lock assemblycontroller board 1540, the operation of the dead bolt drive shaft 1533can be controlled in response to iris match determination signals thatthe door lock assembly controller board 1540 receives from the irisbiometric recognition module 1514. For example, referring to FIG. 1, ifthe iris biometric recognition module 1514 determines that the “iriscode” derived from an image of an iris of the human subject 1424 doesnot match any of the iris codes in a collection of reference iris codes,the door lock assembly controller 1540 may activate the motor 1536 to,via the dead bolt drive shaft 1533, move the dead bolt 1532 into alocked position. Conversely, if the iris biometric recognition module1514 determines that the iris code of the human subject 1424 does matcha reference iris code, the door lock assembly controller 1540 mayactivate the motor 1536 to, via the dead bolt drive shaft 1533, move thedead bolt 1532 into an unlocked position. Of course, the oppositefunctionality is implemented in other embodiments. That is, the doorlock controller 1540 may be configured so that the dead bolt 1532 locksthe door (e.g., the door 1416) if an iris match is detected and unlocksthe door 1416 if an iris match is not detected.

Components of the door lock assembly 1500, such as the outer assembly1510, the access control structure 1526, the inner assembly 1552, and/orothers, are made of a material that is suitable according to thecorresponding functionality of the component (e.g., plastic or, in thecase of the latch 1530 and bolt 1532, stainless steel or other metal).When the door lock assembly 1500 is fully assembled, the componentsshown in FIG. 15, including the iris biometric recognition module 1514,are contained in a single unitary device that can be installed in theaccess control structure (e.g., door) 1416, in another form ofingress/egress control device, or in any other type of device or systemthat can benefit from the use of iris biometric recognition technology.

Referring now to FIGS. 16-17, the illustrative iris biometricrecognition module 1514 is shown in greater detail. As shown in FIG. 16,when assembled, the iris biometric recognition module 1514 is aself-contained unitary module. As such, the iris biometric recognitionmodule 1514 can be incorporated into not only door lock assemblies, butany other type of device, apparatus, article, or system that can benefitfrom an application of iris biometric recognition technology. The irisbiometric recognition module 1514 includes a support base 1610, to whichan iris biometric recognition controller 1724 is mounted. A number ofsupport posts, e.g., posts 1612, 1613, 1614, 1616, are coupled to thesupport base 1610 (by, e.g., a corresponding number of screws or otherfasteners 1730, 1731, 1732, 1733) (1733 not shown). The support posts1612, 1613, 1614, 1616 are connected to and support a pivot mount base1618.

Coupled to and supported by the pivot mount base 1618 are an iris imagerassembly 1626 and a face imager assembly 1628. In some embodiments, theiris imager assembly 1626 and the face imager assembly 1628 are the samedevice or utilize one or more of the same components (e.g., the sameimaging device). However, in the illustrative embodiment, the irisimager assembly 1626 and the face imager assembly 1628 are separateassemblies utilizing different components. As described in more detailbelow, the face imager assembly 1628 captures digital images of a humansubject, and more particularly, images of the subject's face and eyes,using a face imager 1648 that is equipped with a wide field of viewlens. The iris imager assembly 1626 captures digital images of an irisof an eye of the human subject using an iris imager 1644 that isequipped with a narrow field of view lens. In some embodiments, both theface imager 1648 and the iris imager 1644 utilize the same type ofimager (e.g., a digital camera, such as the Omnivision model no.OV02643-A42A), equipped with different lenses. For example, the faceimager 1648 may be equipped with a wide field of view lens such as theSenview model no. TN01920B and the iris imager 1644 may be equipped witha narrow field of view lens such as model no. JHV-8M-85 by JA HWAElectronics Co. In other embodiments, a single high resolution imager(e.g., a 16+ megapixel digital camera) may be used with a wide field ofview lens (rather than a combination of two cameras with differentlenses) to perform the functionality of the iris imager 1644 and theface imager 1648.

The illustrative iris imager assembly 1626 is pivotably coupled to thepivot mount base 1618 by an axle 1622. The axle 1622 is e.g. removablydisposed within a pivot groove 1620. The pivot groove 1620 is defined inthe pivot mount base 1618. The components of the iris imager assembly1626 are mounted to an iris pivot mount base 1630. The iris pivot mountbase 1630 is coupled to the axle 1622 and to a support tab 1734. Thesupport tab 1734 is coupled to a lever arm 1726 by a pivot link 1728.The lever arm 1726 is coupled to a control arm 1722. The control arm1722 is driven by rotation of an output shaft of a motor 1720. The motor1720 may be embodied as, for example, a servo motor such as a magneticinduction brushless servo motor (e.g., the LTAIR model no. D03013).Operation of the motor 1720 rotates the control arm 1722, which causeslinear motion of the lever arm 1726, resulting in linear motion of thetab 1734. The linear motion of the tab 1734 rotates the axle 1622 in thepivot groove 1620. Depending on the direction of rotation of the outputshaft of the motor 1720, the resulting rotation of the axle 1622 in thepivot groove 1620 causes the iris pivot mount base 1630 to tilt in onedirection or the other, with respect to the pivot mount base 1618. Forexample, clockwise rotation of the motor output shaft may result in theiris pivot mount base 1630 tilting in an upwardly direction toward theface imaging assembly 1628 and vice versa. This pivoting capability ofthe iris pivot mount base 1630 enables the position of the iris imagingassembly 1626 to be mechanically adjusted to accommodate potentiallywidely varying heights of human subjects (e.g., the human subject 1424),ranging from small children to tall adults. In other embodiments,however, the iris imager assembly 1626 is stationary with respect to thepivot mount base 1618 and the ability to detect the irises of humansubjects of widely varying heights is provided by other means, e.g., bysoftware or by the use of a column of vertically-arranged iris imagers1644 coupled to the mount base 1618.

The components of the iris imaging assembly 1626 include the iris imager1644, a filter 1646 disposed on or covering the iris imager 1644, a pairof iris illuminator assemblies 1710, 1712 each adjacent to, e.g.,disposed on opposite sides of, the iris imager 1644, and a pair ofbaffles or light guides 1636, 1638 disposed between the each of the irisilluminator assemblies 1710, 1712, respectively, and the iris imager1644. Each of the illustrative iris illuminator assemblies 1710, 1712includes one or more infrared light sources, e.g., infrared lightemitting diodes (LEDs). In the illustrative embodiment, each irisilluminator assembly 1710, 1712 includes a number “N” of illuminators1711, where N is a positive integer. While N=4 for both of the irisilluminator assemblies 1710, 1712 in the illustrative embodiment, thenumber N may be different for each assembly 1710, 1712 if required ordesirable for a particular design of the iris biometric recognitionmodule 1514. Each set of N illuminators is bounded by an additionallight guide or shield 1714, 1716. Diffusers 1632, 1634 cover the irisilluminator assemblies 1710, 1712, respectively. For example, thediffusers 1632, 1634 may be coupled to the shields 1714, 1716respectively (e.g., by an adhesive material). In the illustrativeembodiments, the diffusers 1632, 1634 correct for the inherentnon-uniformity of the light emitted by the illuminators 1711 (e.g.,uneven lighting). This non-uniformity may be due to, for example,manufacturing irregularities in the illuminators 1711. As such, thediffusers 1632, 1634 may not be required in embodiments in which higherquality illuminators (or different types of illuminators) 1711 are used.

Although not specifically required for purposes of this disclosure, theillustrative iris imaging assembly 1626 further includes a pair ofvisual cue illuminators 1640, 1642, which are embodied as emitters oflight having a wavelength in the visible light spectrum (e.g., coloredlight LEDs). The baffles 1636, 1638 and the shields 1714, 1716 areconfigured to prevent stray light emitted by the illuminator assemblies1710, 1712 (and, for that matter, the visual cue LEDs 1640, 1642) frominterfering with the operation of the iris imager 1644. That is, thebaffles 1636, 1638 and the shields 1714, 1716 help ensure that wheninfrared light is emitted by the illuminator assemblies 1710, 1712, onlythe emitted light that is reflected by the eyes of the human subject(e.g., human subject 1424) is captured by the iris imager 1644.Additionally, a filter 1646 covers the lens of the iris imager 1644. Thefilter 1646 further blocks any extraneous light from entering the lensof the iris imager 1644. The filter 1646 may be embodied as, forexample, an 840 nm narrowband filter and may be embedded in the lensassembly of the iris imager 1644. In other embodiments, other types offilters may be used, depending on the type of illuminators selected forthe illuminator assemblies 1710, 1712. In other words, the selection ofthe filter 1646 may depend on the type or configuration of theilluminator assemblies 1710, 1722, in some embodiments.

The illustrative face imager assembly 1628 includes a face imager mountbase 1631. The illustrative face imager mount base 1631 is non-pivotablycoupled to the pivot mount base 1618. In other embodiments, however, theface imager mount base 1631 may be pivotably coupled to the pivot mountbase 1618 (e.g., the face imager assembly 1628 and the iris imagerassembly 1626 may both be mounted to the pivot mount 1630), as may bedesired or required by a particular design of the iris biometricrecognition module 1514. The face imager assembly 1628 includes the faceimager 1648 and a face illuminator assembly 1650 located adjacent theface imager assembly 1628. The face imager assembly 1628 and the irisimager assembly 1626 are illustratively arranged so that the face imagerassembly 1628 is vertically above the iris imager assembly 1626 when theiris biometric recognition module 1514 is mounted to a verticalstructure (such as the door 1416). In other words, the face imagerassembly 1628 and the iris imager assembly 1626 are arranged so that theface imager assembly 1628 is positioned adjacent to a first edge of thepivot mount base 1618 and the iris imager assembly 1626 is positionedadjacent to another edge of the pivot mount base 1618 that is oppositethe first edge.

The face imager 1648 is secured to the face imager mount base 1631 by abracket 1633. The face illuminator assembly 1650 includes one or moreinfrared light sources 1649 (e.g., infrared LEDs) mounted to a concavelyshaped illuminator mount base 1740. In the illustrative embodiment, theface illuminator assembly 1650 includes a number “N” of illuminators1649, where N is a positive integer (e.g., N=4). The configuration ofthe mount base 1740 enables the illuminators 1649 to be arranged at anangle to one another, in order to illuminate the desired portion of thecapture zone (e.g., the range of vertical heights H1 of the eye levelsof the anticipated population of human subjects 1424). The illuminators1649 of the face illuminator assembly 1650 and the illuminators 1711 ofthe iris illuminator assemblies 1710, 1712 may each be embodied as ahigh power 840 nm infrared emitter (e.g., model no. OV02643-A42Aavailable from OSRAM Opto Semiconductors).

The illustrative iris biometric recognition controller 1724 is embodiedas an integrated circuit board including a microprocessor (e.g., modelno. MCIMX655EVM10AC available from Freescale Semiconductor). The irisbiometric recognition controller 1724 is configured to control andcoordinate the operation of the face illuminator assembly 1650, the faceimager 1648, the iris illuminator assemblies 1710, 1712, and the irisimager 1644, alone or in combination with other components of the irisbiometric recognition module 1514.

Referring now to FIG. 18, an embodiment 1800 of an irisbiometric-enabled access control system is shown. The irisbiometric-enabled access control system 1800 is shown in the context ofan environment 1810 that may be created during the operation of the irisbiometric recognition module 1514 (e.g., a physical and/or virtualexecution or “runtime” environment). As shown in the environment 1810,in addition to the hardware components described above, the irisbiometric recognition module 1514 includes a number of computer programcomponents 1818, each of which is embodied as machine-readableinstructions, modules, data structures and/or other components, and maybe implemented as computer hardware, firmware, software, or acombination thereof, in memory of the controller board 1724, forexample.

The iris biometric recognition module computer program components 1818include an iris image capture module 1820. The illustrative iris imagecapture module 1820 includes a face finder module 1822, an iris findermodule 1824, a face/iris imager control module 1826, and a face/irisilluminator control module 1828. In operation, the face/iris imagercontrol module 1826 controls a face/iris imager 1812 (e.g., the faceimager 1648 and/or the iris imager 1644) by transmitting face imagercontrol signals 1842 to the face/iris imager 1812 to capture digitalimages of a human subject 1804 entering or located in a tracking andcapture zone 1802. In some embodiments, the iris biometric recognitionmodule 1514 may be equipped with a motion sensor that can detect thehuman subject 1804 in the tracking and capture zone 1802. In thoseembodiments, the face/iris imager control module 1826 may initiateoperation of the face/iris imager(s) 1812 in response to a motiondetection signal received from the motion sensor. In other embodiments,the presence of a human subject 1804 can be detected using an imageprocessing routine that recognizes a face in the field of view of theface/iris imager 1812. As noted above, the iris biometric recognitionmodule 1514 can utilize iris images captured from moving subjects and/orsubjects that are at a distance that is greater than, e.g., 45 cm awayfrom the iris imaging device.

The illustrative face finder module 1822 executes a face recognitionalgorithm (e.g., FaceRecognizer in OpenCV), to determine whether animage captured by the face/iris imager 1812 (e.g., by a wide field ofview camera) includes a human face. If the face finder module 1822detects a human face, the face finder module 1822 returns the facelocation 1848, e.g., bounding box coordinates of the detected facewithin the captured image. In response to the face detection, theface/iris imager control module 1826 configures the face/iris imager1812 to capture an image of an iris of the detected face. To do this,the illustrative face/iris imager control module 1826 may compute thetilt angle by which to tilt the iris imager assembly 1626 based on thebounding box coordinates of the detected face. This can be done byapproximating the linear distance from the face/iris imager 1812 to thedetected face, if the location and the field of view of the face/irisimager 1812 are known. For example, the proper tilt angle for theface/iris imager 1812 can be derived from the geometry of the triangleformed by connecting the location of the face/iris imager 1812 to thetop and bottom edges of the bounding box of the detected face.

Once the tilt angle for the face/iris imager 1812 is determined, theface/iris imager control module 1826 operates the motor 1720 to achievethe computed tilt angle of the face/iris imager 1812. Once the face/irisimager 1812 is properly positioned with respect to the detected face,the iris finder module 1824 locates an eye and then the iris of the eye,on the human face, by executing eye and iris detection algorithms (e.g.,the algorithms mentioned above with reference to FIGS. 1-13). Inresponse to receiving iris location information 1850 from the irisfinder module 1824, the face/iris imager control module 1826 initiatesthe process of capturing images of the iris by transmitting iris imagercontrol signals 1842 to the face/iris imager 1812. These iris detectionand image capture processes can be performed, for example, using thetechniques described above with reference to FIGS. 1-13.

In capturing images of the face and iris of the detected human subject,the iris image capture module 1820 interfaces with a face/irisilluminator control module 1828 to coordinate, e.g., synchronize 1852,the operation of the face/iris imager 1812 and face/iris illuminators1818. During the face image capture process, the control modules 1826,1828 synchronize the operation of the face illuminator assembly 1650with the capturing of face images by the face imager 1648. This helpsensure consistent face image quality irrespective of the availableambient lighting conditions. In other words, the coordination of theface image capture and the operation of the face illuminator assembly1650 is analogous to traditional flash photography, albeit usinginfrared light rather than visible light. Additionally, during theprocess of capturing the iris images, the control modules 1826, 1828synchronize the operation of the iris illuminators 1816 (e.g., irisilluminator assemblies 1710, 1712) with the capturing of iris images bythe iris imager 1644. To accommodate the possibility that the subject1804 may be moving, the iris imager control module 1826 operates theiris imager 1644 using a focal sweep technique in which several (e.g.,10-15 or more) images of the iris are captured in rapid succession(e.g., at a shutter speed in the range of about 5 frames per second).Synchronously, the iris illuminator control module 1828 pulses/strobesthe iris illuminators 1710, 1712 at the same rate/frequency. This helpsensure that at least one good quality iris image is obtainedirrespective of the available ambient lighting conditions and regardlessof whether the subject is moving or whether the view of the iris isobstructed or distorted. In other words, the coordination of the irisimage capture and the operation of the iris illuminators 1710, 1712 isanalogous to traditional “red eye reduction” flash photography, exceptthat the images of the iris are taken at the same time as thepulsing/strobing of the iris illuminators 1710, 1712 rather than afterthe pulsing/strobing is completed (and also, using infrared illuminatorsrather than visible light).

The iris image capture module 1820 outputs or otherwise makes availablethe resulting iris images 1854 to an iris image processing and matchingmodule 1830. The iris image processing and matching module 1830processes the images by, e.g., removing portions of the image thatdepict eyelids and eyelashes and adjusting for enlarged pupils, andproducing the “iris code” in, for example, the manner described abovewith reference to FIGS. 1-13. The iris image processing and matchingmodule 1830 compares the processed iris images 1854 or usable portionsthereof, or the iris code, to reference image data 1836, to determinewhether any of the captured iris images 1854 match an image stored inthe reference images 1836. The reference image data 1836 includes irisimage samples and/or related data that has been obtained previously,e.g., through an enrollment procedure. If the iris images 1854 are notfound to match any of the images in the reference images data 1836, theiris image processing and matching module 1830 may initiate anenrollment procedure. That is, the iris biometric recognition module1514 can be configured to perform iris image enrollment directly at thedevice, if required or desired for a particular implementation. To dothis, the iris image processing and matching module 1830 passes thecollected iris image(s) 1862 to an iris image enrollment module 1834. Tocomplete the enrollment process, the illustrative iris image enrollmentmodule 1834 may execute an image quality analysis on one or more of thereference image candidates 1862. An iris image may be added to thereference images data 1836 if the image quality analysis indicates thatthe image is suitable for use as a reference image. In performing theimage quality analysis, the iris image enrollment module 1834 mayanalyze a number of different image quality factors, such as: the amountof the iris that is exposed in the image (e.g., the person is notsquinting or blinking), the sharpness of the image, and the number ofartifacts in the image (e.g., the number of eyelashes, specularities,etc.).

As a result of the iris image processing and matching performed by themodule 1830, the iris biometric recognition module 1514 outputs orotherwise makes available an iris match determination 1856. The irismatch determination 1856 may be embodied as a simple “positive” or“negative” indication, or may include other information (such asperson-identifying information connected with the matched iris image),alternatively or in addition. In the illustrative access control system1800, an access control module 1832 (e.g., the door lock controller1540) executes business logic encoded as, e.g., computer program logic,to determine how or even whether the access control system 1800 shouldrespond to the iris match determination data 1856. For example, theaccess control system 1800 may send a lock or unlock signal to an accesscontrol mechanism (such as the motor 1536). Alternatively or inaddition, the access control module 1832 may issue an electronicnotification to another device or system. For instance, the accesscontrol module 1832 may send an alert to a building security system, ormay transmit a lock signal to other door lock assemblies in the samefacility. In other contexts, the access control module 1832 may enableor disable certain other electronic features of a device in response tothe iris match determination 1856. As an example, the access controlmodule 1832 may, in response to a positive iris match, unlock a car doorand configure features of a vehicle infotainment system based on, e.g.,personal profile information associated with the positive iris match.Similarly, the access control module 1832 may, in response to a negativeiris match, lock a safe, a liquor cabinet or a refrigerator and send anotification to a homeowner's personal electronic device (e.g., asmartphone or tablet computer).

Referring now to FIG. 19, an example of a method 1900 executable by oneor more components of the iris biometric recognition module 1514. Themethod 1900 may be embodied as computerized programs, routines, logicand/or instructions, which may be embodied in hardware, software,firmware, or a combination thereof, of the iris biometric recognitionmodule 1514 and/or one or more other systems or devices in communicationwith the iris biometric recognition module 1514. In block 1910, themodule 1514 detects a human subject approaching the iris biometricrecognition module 1514. To do this, the module 1514 may analyze signalsreceived from a wide field of view camera (e.g., the face imager 1648)or may analyze signals received from a motion sensor monitoring acapture zone of the iris biometric recognition module 1514. In block1912, the module 1514 locates the face and eyes of the approachingsubject in relation to a ground plane and in relation to the irisbiometric recognition module 1514. To do this, the module 1914 may, inblock 1914, control the face illuminators 1649 to illuminate (withinfrared light) the area in which the human subject, or moreparticularly, the subject's face, is detected.

Once the subject's face is located, in block 1916, the module 1514configures the iris imager 1644 to collect images of an iris of an eyeof the approaching subject. As noted above, configuring the iris imagermay involve operating a motor to tilt a platform to which the irisimager is mounted. Alternatively, the configuring may be performed e.g.by software controlling the lens focus and/or field of view of the irisimager. In any event, the procedure of block 1916 aligns the iris imagerwith the eye (or more particularly the iris) of the approaching subject.

In some embodiments, in block 1918, the module 1514 activates the visualcue illuminators 1640, 1642, to try to draw the subject's attention orvisual focus toward the iris biometric recognition module 1514. Thevisual cue illuminators 1640, 1642 are typically activated after thesubject's face is detected and the iris imager is configured (e.g.,mechanically positioned), in order to draw the subject's eyes in-linewith the iris imager camera.

Once the subject's face and eyes are detected, the iris biometricrecognition module 1514 enters a loop 1920 in which the module 1514coordinates the operation of the iris illuminator and the iris imager inrapid succession to obtain multiple images of the iris (e.g., frame rateof the iris imager and short-duration pulse frequency of the irisilluminator are coordinated/synchronized). More specifically, in block1922, the module 1514 causes the iris illuminator assemblies to issueshort pulses of high intensity infrared light. As discussed above withreference to FIGS. 1-13, in some embodiments of the module 1514, a lightintensity of the illumination source (e.g., illuminators 1711) isincreased during strobe to maintain a predetermined signal-to-noise(S/N) ratio, while an average irradiance of the illumination source overthe course of the strobing remains below a safety threshold. Atsubstantially the same time, the module 1514 causes the iris imager tocapture a series of images of the pulse-illuminated iris (using, e.g., a“focal sweep” technique). That is, the iris image captures are timed tosubstantially coincide with the short, high intensity pulses ofillumination, resulting in a “freeze” effect on the subject if thesubject is in motion. In other embodiments, other alternatives to thefocal sweep technique can be used, e.g.: auto focus on a target spot, ifthe subject is standing still for a length of time, or by using a fixedlens to provide a large fixed focus area.

In block 1926, the module 1514 determines whether to use any of thecaptured iris images are candidates to be used for enrollment purposes.If an iris image is a candidate to be used for enrollment, the module1514 performs an iris image quality analysis on the image in block 1928,and updates the reference database of iris images if the qualityanalysis is successful.

In blocks 1930, 1932, and 1934, the module 1514 performs iris imageprocessing and matching in accordance with, for example, the techniquesdescribed above with reference to FIGS. 1-13. In block 1930, the module1514 selects a subset of the captured iris images for matching purposes,based on image quality, size of the iris depicted in the image, and/orother factors. In block 1932, the module 1514 identifies a usableportion of the iris image(s) selected in block 1930 (using, e.g., thesegmentation techniques described above). The “usable portion” of aniris image may correspond to the iris code, in some embodiments. Inblock 1934, the module 1514 compares the usable portion of the irisimage identified in block 1932 to one or more reference images (e.g.,the reference images 1836). In block 1936, the module 1514 determineswhether the comparison performed in block 1934 results in an iris match.

An “iris match” as determined by the module 1514 may refer to, amongother things, a numerical score that represents the probability that thecaptured iris image corresponds to the known iris image of a specificperson. The “iris match” parameters are tunable, and can be set, forexample, based on the accuracy requirements of a particularimplementation of the module 1514 (e.g., how stringent is the test foracceptance of the subject as matching the identity of a known subject).As mentioned above with reference to FIGS. 1-13, the illustrative module1514 computes a Hamming distance between an iris code representative ofthe captured iris image and the iris code representative of a referenceiris image. In information theory, the Hamming distance between twostrings of equal length is the number of positions at which thecorresponding symbols are different. Put another way, the Hammingdistance measures the minimum number of substitutions required to changeone string into the other, or the number of errors that transformed onestring into the other. So, for example, if the module 1514 uses aHamming distance of 0.35, that corresponds to a 1:133,000 false acceptrate. Similarly, if the module 1514 is configured to use a Hammingdistance of 0.28, the false accept rate is 1:10E11.

If the module 1514 determines in block 1936 that there is an iris match,the module 1514 outputs a match signal that can be used by an accesscontrol assembly to initiate access control logic for a positive matchin block 1938 (e.g., unlock the door 1416). If the module 1514determines in block 1936 that there is not an iris match, the module1514 outputs a “no match” signal (or the absence of a signal may also beused as a no-match indication), which can be used by an access controlassembly to initiate access control logic for a negative match condition(e.g., lock the door 1416).

Example Usage Scenarios

Numerous applications of the disclosed technology exist that wouldbenefit if the user and/or subject who is at a location, accessing anobject, entering a premises, etc. could be accurately authenticated,verified, identified, or biometrically recorded at that instance of timefor a variety of reasons. Many of these instances do not require one toknow who the person is at that time. To date, this has not been possibledue to the cumbersome nature of creating a biometric record and/oraccurately matching to an existing template for the user or subject.

Today, documenting/recording the presence of an individual at a locationat a moment in time is typically managed by the individual beingidentified by another person by sight, via a set of questions, and/orthe person inspecting credentials such as a passport, driver license,employee badge, etc. (which must be validated) presented by theindividual or recording a video or photograph of the individual at thatlocation. None of these approaches is entirely accurate. The process ofinspecting the credentials only validates the credentials presented. Itdoes not validate that the person holding those credentials is actuallythe person described on the credentials. In addition, videos and photoscan be easily manipulated to inaccurately record or misrepresent thepresence of a person at a specific location.

The ability to record the presence of a user or subject by using an irisbiometric collection device (which may be incorporated into another typeof device, such as a fixed or mobile electronic device) that uses strobeillumination above the continuous wave eye safe limit would allow thedocumentation that the actual person was at that location, accessed anitem, used a service, or obtained a benefit at the specific time. Theuse of the strobe illumination above the continuous wave eye safe limitsallows collection of the biometric image in all lighting conditions(indoor, outdoor, bright sunlight, extreme darkness) and withoutrequiring the subject or user to be stationary. Unlike existingbiometric iris readers, the disclosed devices can be equipped with wiredand/or wireless connectivity to maintain the most recent data on thedevice. Use of the iris as the enabling biometric allows identity to bedetermined without touching the subject as in a fingerprint and is lessobtrusive than other biometric identification modalities. Theimplementations disclosed herein allow the collection of a high qualityrecord with cooperative or uncooperative subjects including covertoperations. Recording of the person's iris at a location at a specifictime can be used verifiable proof that the specific person was at aparticular location. The relevant location information can be capturedas well (e.g., by a Global Positioning System or cellular location-basedsystem), and stored along with the iris image and/or associatedinformation. The biometric collection device described may be used aloneor in conjunction with other collection and authentication techniques(e.g., PIN, pattern, different biometric) if multi-levels ofauthentication are desired.

Examples of events, activities or locations where the ability todocument/record the presence or access of a person(s) to the location ata specific times are as follows: safes and safety deposit boxes;amusement parks; animal tagging and tracking (domestic, wild, aquatic,etc.); appliances (refrigerator, oven, gym equipment); assisted livingfacilities; automated teller machine; automated gate control; backgroundchecks; blood donors/red cross; brokerage account; casino; check cashingagencies; child day care facilities; commercial shipping facility;cruise ships; datacenter cabinets; detox centers; document screeningactivity; driver vehicle enrollment; drug testing collection location;entertainment facilities (club, theater, concert hall, skyboxes,stadiums, etc.); entitlement programs activities; ez pass authorization;fire drills; first responders securing an event; gun access; half-wayhouses; health club/gym/spa; hospitals; hotels/motels; insurance claimvalidations; large clinical studies; law enforcement activities;library; medical lab (quest/labcorp); mining operations; paroletracking; patient history; pay per usage; prisons; property storagelocations; real-time monitoring of person using computer; refugetracking; rehabilitation clinics; resorts; retail services; schools;shopper loyalty; ski lifts; sporting events; tax preparing and payingservices; tele-medical services; tradeshow/conferences; validation ofservice personnel; vehicle management; voting and petitions; workforcemanagement, and/or others.

Implementation Examples

Referring now to FIG. 20, a simplified block diagram of an irisbiometric recognition-enabled system 2000 is shown. While theillustrative embodiment 2000 is shown as involving multiple componentsand devices, it should be understood that the system 2000 may constitutea single device, alone or in combination with other devices. The system2000 includes an iris biometric recognition module 2010, an irisbiometric-controlled mechanism 2050, one or more other devices and/orsystems 2062, and a server computing device 2070. Each or any of thedevices/systems 2010, 2050, 2062, 2070 may be in communication with oneanother via one or more electronic communication links 2048.

The system 2000 or portions thereof may be distributed across multiplecomputing devices as shown. In other embodiments, however, allcomponents of the system 2000 may be located entirely on, for example,the iris biometric recognition module 2010 or one of the devices 2050,2062, 2070. In some embodiments, portions of the system 2000 may beincorporated into other systems or computer applications. Suchapplications or systems may include, for example, commercial off theshelf (COTS) or custom-developed cameras, operating systems,authentication systems, or access control systems. As used herein,“application” or “computer application” may refer to, among otherthings, any type of computer program or group of computer programs,whether implemented in software, hardware, or a combination thereof, andincludes self-contained, vertical, and/or shrink-wrapped softwareapplications, distributed and cloud-based applications, and/or others.Portions of a computer application may be embodied as firmware, as oneor more components of an operating system, a runtime library, anapplication programming interface (API), as a self-contained softwareapplication, or as a component of another software application, forexample.

The illustrative iris biometric recognition module 2010 includes atleast one processor 2012 (e.g. a microprocessor, microcontroller,digital signal processor, etc.), memory 2014, and an input/output (I/O)subsystem 2016. The module 2010 may be embodied as any type ofelectronic or electromechanical device capable of performing thefunctions described herein. Although not specifically shown, it shouldbe understood that the I/O subsystem 2016 can include, among otherthings, an I/O controller, a memory controller, and one or more I/Oports. The processor 2012 and the I/O subsystem 2016 are communicativelycoupled to the memory 2014. The memory 2014 may be embodied as any typeof suitable computer memory device, including fixed and/or removablememory devices (e.g., volatile memory such as a form of random accessmemory or a combination of random access memory and read-only memory,such as memory cards, e.g., SD cards, memory sticks, hard drives, and/orothers).

The I/O subsystem 2016 is communicatively coupled to a number ofhardware and/or software components, including computer programcomponents 1818 such as those shown in FIG. 18 or portions thereof,illuminator(s) 2030 (e.g., face and iris illuminators 1816), an imagingsubsystem 2032 (which may include separate face and iris imagers 2034,2036), a motor 2038, and one or more motion and/or location sensors2040. As used herein, an “imager” or “camera” may refer to any devicethat is capable of acquiring and recording two-dimensional (2D) orthree-dimensional (3D) still or video images of portions of thereal-world environment, and may include cameras with one or more fixedcamera parameters and/or cameras having one or more variable parameters,fixed-location cameras (such as “stand-off” cameras that are installedin walls or ceilings), and/or mobile cameras (such as cameras that areintegrated with consumer electronic devices, such as laptop computers,smart phones, tablet computers, wearable electronic devices and/orothers.

The I/O subsystem 2016 is also communicatively coupled to one or moredata storage devices 2020, a communication subsystem 2028, a userinterface subsystem 2042, and a power supply 2044 (e.g., a battery). Theuser interface subsystem 2042 may include, for example, hardware orsoftware buttons or actuators, a keypad, a display device, visual cueilluminators, and/or others. It should be understood that each of theforegoing components and/or systems may be integrated with the module2010 or may be a separate component or system that is in communicationwith the I/O subsystem 2016 (e.g., over a network or a bus connection).In some embodiments, the UI subsystem 2042 includes a push button orsimilar mechanism for initiating the iris image enrollment processdescribed above. In other embodiments, the iris image enrollment processtakes place off the module 2010, e.g., on another device, such as adesktop computing device. Alternatively or in addition, iris imageenrollment capabilities can be provided at a “central” module or servercomputer and then propagated to other modules 2010, e.g., via acommunications network. For instance, in access control applications,enrollment may take place at a main entrance to a facility or securitycommand center. Privileges can be determined at the central module orserver and then pushed out to or “downloaded” by the individual doorlock assemblies in the facility.

The data storage device 2020 may include one or more hard drives orother suitable data storage devices (e.g., flash memory, memory cards,memory sticks, and/or others). In some embodiments, portions of thesystem 2000 containing data or stored information, e.g., a database ofreference images 1836, iris matching data/rules 2024 (e.g., accesscontrol logic or business logic for determining when an iris match hasoccurred and what to do when an iris match does or does not occur), irisimager configuration data/rules 2026 (e.g., mapping tables or functionsfor mapping iris imager tilt angles to motor control parameters), and/orother data, reside at least temporarily in the storage media 2020.Portions of the system 2000, e.g., the iris image database 2022, theiris matching data/rules 2024, the iris imager configuration data/rules2026, and/or other data, may be copied to the memory 2014 duringoperation of the module 2010, for faster processing or other reasons.

The communication subsystem 2028 communicatively couples the module 2010to one or more other devices, systems, or communication networks, e.g.,a local area network, wide area network, personal cloud, enterprisecloud, public cloud, and/or the Internet, for example. Accordingly, thecommunication subsystem 2028 may include a databus, datalink, one ormore wired or wireless network interface software, firmware, orhardware, for example, as may be needed pursuant to the specificationsand/or design of the particular embodiment of the module 2010.

The iris biometric-controlled mechanism 2050, the otherdevice(s)/system(s) 2062, and the server computing device 2070 each maybe embodied as any suitable type of computing device, electronic device,or electromechanical device capable of performing the functionsdescribed herein, such as any of the aforementioned types of devices orother electronic devices. For example, in some embodiments, the servercomputing device 2070 may operate a “back end” portion of the irisbiometric computer program components 1818, by storing the referenceimages 1836, iris matching data/rules 2024, and/or iris imagerconfiguration data/rules 2026, in a data storage device 2080 or byperforming other functions of the module 2010. In general, components ofthe server computing device 2070 having similar names to components ofthe module 2010 described above (e.g., processor 2072, memory 2074, I/Osubsystem 2076) may be embodied analogously. The illustrative servercomputing device 2070 also includes a user interface subsystem 2082, acommunication subsystem 2084, and an iris image enrollment system 2078(which may capture and evaluate iris images for enrollment purposes,similar to the iris image enrollment module 1834 described above).

Further, each of the mechanisms/devices/systems 2050, 2062 may includecomponents similar to those described above in connection with themodule 2010 and/or the server computing device 2070, or another type ofelectronic device (such as a portable electronic device, embedded system(e.g., a vehicle infotainment system or smart appliance system). Forexample, the iris biometric-controlled mechanism 2050 includes one ormore processors 2052, memory 2054, and an I/O subsystem 2056 (analogousto the processor 2012, memory 2014, and I/O subsystem 2016), an on-boardpower supply 2058 (e.g., a battery), and an access control module 1832(e.g., to perform access control logic in response to an iris matchdetermination made by the module 2010). The system 2000 may includeother components, sub-components, and devices not illustrated in FIG. 20for clarity of the description. In general, the components of the system2000 are communicatively coupled as shown in FIG. 20 by one or moreelectronic communication links 2048, e.g., signal paths, which may beembodied as any type of wired or wireless signal paths capable offacilitating communication between the respective devices andcomponents, including direct connections, public and/or private networkconnections (e.g., Ethernet, Internet, etc.), or a combination thereof,and including short range (e.g., Near Field Communication) and longerrange (e.g., Wi-Fi or cellular) wireless communication links.

Additional Examples

Illustrative examples of the technologies disclosed herein are providedbelow. An embodiment of the technologies may include any one or more,and any combination of, the examples described below.

In an example 1, an iris biometric recognition module includes a base;an iris imager assembly supported by the base; a processor supported bythe base and in electrical communication with the iris imager assembly;and a non-transitory storage medium supported by the base and readableby the processor, the non-transitory storage medium having embodiedtherein a plurality of instructions executable by the processor to causethe iris biometric recognition module to: with the iris imager assembly,capture an iris image, the iris image depicting at least a portion of aniris of an eye of a human subject detected in a capture zone, whereinthe capture zone is to include an area that is spaced from the irisbiometric recognition module by a distance in the range of at leastabout forty-five centimeters; with the processor, compare dataindicative of the captured iris image to reference iris data; and withthe processor, based on the comparison of the data indicative of thecaptured iris image to the reference iris data, output a signalindicative of an iris match determination.

An example 2 includes the subject matter of example 1, wherein thecapture zone includes an area having a vertical height in the range ofabout three feet to about seven feet above a ground plane. An example 3includes the subject matter of example 1 or example 2, wherein theinstructions are executable to cause the iris biometric recognitionmodule to capture the iris image while the human subject is in motion,compare data indicative of the iris image captured while the humansubject is in motion to reference iris data; and based on the comparisonof the data indicative of the iris image captured while the humansubject is in motion to the reference iris data, output a signalindicative of an iris match determination. An example 4 includes thesubject matter of example any of examples 1-3, wherein the iris imagerassembly includes a narrow field of view imager, and the instructionsare executable to configure the narrow field of view imager to focus onthe iris of the eye of the human subject. An example 5. includes thesubject matter of example of any of examples 1-4, wherein the irisimager assembly is pivotably coupled to the base, and the instructionsare executable to pivot the iris imager assembly relative to the base.An example 6 includes the subject matter of example 5, wherein the irisimager assembly includes a wide field of view imager and theinstructions are executable to cause the wide field of view imager todetect the face of the human subject, estimate a location of the face ofthe human subject in relation to a ground plane, and, based on theestimated location of the face of the human subject in relation to theground plane, determine an amount by which to pivot the iris imagerassembly. An example 7 includes the subject matter of any of examples1-6, wherein the iris imager assembly includes an illuminator and animager, and the instructions are executable to substantially synchronizepulsed illumination by the illuminator and iris image capture by theimager using a focal sweep technique.

In an example 8, an iris biometric recognition module includes: a base;an iris imaging subsystem supported by the base; a processor inelectrical communication with the iris imaging subsystem; anon-transitory storage medium readable by the processor, thenon-transitory storage medium having embodied therein a plurality ofinstructions executable by the processor to cause the iris biometricrecognition module to: capture an image of an iris of an eye of a humansubject in a capture zone; compare data indicative of the captured irisimage to reference iris data; and output a signal indicative of an irismatch determination.

An example 9 includes the subject matter of example 8, wherein the irisimaging subsystem includes an iris imager assembly supported by thebase. An example 10 includes the subject matter of example 9, whereinthe iris imager assembly includes an infrared iris illuminator assemblyand a narrow field of view imager adjacent the iris illuminatorassembly. An example 11 includes the subject matter of example 10,wherein the infrared iris illuminator assembly includes a plurality ofinfrared light emitting diodes. An example 12 includes the subjectmatter of example 11, and includes a baffle disposed between theinfrared light emitting diodes and the narrow field of view imager. Anexample 13 includes the subject matter of example 12, and includes adiffuser covering the infrared light emitting diodes of the infrarediris illuminator assembly. An example 14 includes the subject matter ofany of examples 10, 11, 12, or 13, wherein the infrared iris illuminatorassembly includes first and second arrangements of infrared lightemitting diodes, and the narrow field of view imager is disposed betweenthe first and second arrangements of infrared light emitting diodes. Anexample 15 includes the subject matter of any of examples 10, 11, 12,13, or 14, wherein the iris imager assembly includes a visual cueilluminator adjacent the narrow field of view imager. An example 16includes the subject matter of any of examples 10, 11, 12, 13, 14, or15, wherein the iris imager assembly is pivotably coupled to the base.An example 17 includes the subject matter of example 16, and includes amotor coupled to the iris imager assembly by a pivot linkage. An example18 includes the subject matter of any of examples 8-17, wherein the irisimaging subsystem includes an iris imager assembly supported by the baseand a face imager assembly supported by the base. An example 19 includesthe subject matter of example 18, wherein the face imager assemblyincludes an infrared face illuminator assembly and a wide field of viewimager adjacent the infrared face illuminator assembly. An example 20includes the subject matter of example 19, wherein the infrared faceilluminator assembly includes a plurality of infrared light emittingdiodes supported by a concavely shaped mount base. An example 21includes the subject matter of any of examples 18-20, wherein the faceimager assembly is adjacent the iris imager assembly, the iris imagerassembly is pivotably coupled to the base and the face imager assemblyis non-pivotably coupled to the base. An example 22 includes the subjectmatter of any of examples 18-21, wherein the face imager assembly andthe iris imager assembly are embodied in a single imaging device.

In an example 23, an iris biometric access control system includes: oneor more non-transitory machine readable storage media, and, embodied inthe one or more non-transitory machine readable storage media: an irisimage capture module to by a face imager, detect the presence of a humanface in a capture zone defined at least in part by a field of view ofthe face imager; in response to detection of the human face in thecapture zone, align a lens of an iris imager with an iris of thedetected human face; operate an illuminator to illuminate the iris; andoperate the iris imager to produce a plurality of digital images; and aniris image processing and matching module to: select one or more of thereceived iris images for matching; extract a usable portion from each ofthe selected iris images; compare the extracted portion of each of theselected iris images to a reference iris image; and in response to thecomparison of the extracted portions of the selected images and thereference image, operate an access control mechanism.

An example 24 includes the subject matter of example 23, wherein theiris image capture module is to align the iris imager with the iris ofthe detected human face by operating a motor. An example 25 includes thesubject matter of example 23 or example 24, wherein the iris imagecapture module is to substantially synchronously operate the illuminatorand the iris imager to produce the plurality of digital images of theiris.

In an example 26, a door lock assembly includes: a housing, and,supported by the housing: a door lock mechanism; and an iris biometricrecognition module in communication with the door lock mechanism.

An example 27 includes the subject matter of example 26, and includes acover coupled to the housing, wherein the cover and the housing definean interior region, and the iris biometric recognition module isdisposed within the interior region. An example 28 includes the subjectmatter of example 27, wherein the cover includes a window positionedadjacent the iris biometric recognition module and the window is made ofa material that transparent to infrared light. An example 29 includesthe subject matter of any of examples 26-28, wherein the iris biometricrecognition module includes a power supply, and powered by the powersupply: an iris imager assembly and an iris imager control module incommunication with the iris imager assembly. An example 30 includes thesubject matter of example 29, and includes a pivot support and anelectric motor coupled to the pivot support by a pivot linkage, whereinthe iris biometric recognition module is supported by the pivot member.An example 31 includes the subject matter of example 29 or example 30,wherein the iris imager assembly includes an infrared illuminator and anarrow field of view imager adjacent the infrared illuminator. Anexample 32 includes the subject matter of example 31, wherein the irisimager assembly includes a baffle disposed between the infraredilluminator and the narrow field of view imager. An example 33 includesthe subject matter of any of examples 29-32, and includes a face imagerassembly supported by the housing, wherein the face imager assemblyincludes a wide field of view imager and an infrared illuminatoradjacent the wide field of view imager. An example 34 includes thesubject matter of example 26, and includes a power supply supported bythe housing, wherein the power supply is operably coupled to the doorlock mechanism and the iris biometric recognition module. An example 35includes the subject matter of any of examples 26-34, and includes ahandle supported by the housing, wherein the handle is operably coupledto the door lock mechanism.

In an example 36, a method for operating a door lock in response to irisbiometric recognition, performed by a door lock assembly, includes:detecting a human subject approaching the door lock, and, while thehuman subject is approaching the door lock: operating a face imagerassembly to determine the location of the human subject's face;operating an iris imager assembly to capture a plurality of iris images,each of the iris images depicting at least a portion of an iris of aneye of the human subject; selecting an iris image of the plurality ofiris images; comparing at least a portion of the selected iris image toa reference image; and in response to the comparison of at least aportion of the selected iris image to the reference image, operating thedoor lock.

An example 37 includes the subject matter of example 36, whereinoperating the face imager assembly includes operating an infraredilluminator of the face imager assembly and operating a wide field ofview imager of the face imager assembly. An example 38 includes thesubject matter of example 36 or example 37, wherein operating the irisimager assembly includes coordinating the operation a plurality ofinfrared illuminators of the iris imager assembly with the operation ofan iris imager of the iris imager assembly. An example 39 includes thesubject matter of example 38, and includes substantially simultaneouslyperforming a focal sweep operation with the iris imager and performing apulsing illumination operation with the plurality of infraredilluminators. An example 40 includes the subject matter of any ofexamples 36-39, and includes operating the face imager assembly inresponse to the human subject being detected in the range of at leastabout forty-five centimeters away from the door lock.

General Considerations

In the foregoing description, numerous specific details, examples, andscenarios are set forth in order to provide a more thoroughunderstanding of the present disclosure. It will be appreciated,however, that embodiments of the disclosure may be practiced withoutsuch specific details. Further, such examples and scenarios are providedfor illustration, and are not intended to limit the disclosure in anyway. Those of ordinary skill in the art, with the included descriptions,should be able to implement appropriate functionality without undueexperimentation.

References in the specification to “an embodiment,” etc., indicate thatthe embodiment described may include a particular feature, structure, orcharacteristic, but every embodiment may not necessarily include theparticular feature, structure, or characteristic. Such phrases are notnecessarily referring to the same embodiment. Further, when a particularfeature, structure, or characteristic is described in connection with anembodiment, it is believed to be within the knowledge of one skilled inthe art to affect such feature, structure, or characteristic inconnection with other embodiments whether or not explicitly indicated.

Embodiments in accordance with the disclosure may be implemented inhardware, firmware, software, or any combination thereof. Embodimentsmay also be implemented as instructions stored using one or moremachine-readable media, which may be read and executed by one or moreprocessors. A machine-readable medium may include any mechanism forstoring or transmitting information in a form readable by a machine(e.g., a computing device or a “virtual machine” running on one or morecomputing devices). For example, a machine-readable medium may includeany suitable form of volatile or non-volatile memory.

Modules, data structures, blocks, and the like are referred to as suchfor ease of discussion, and are not intended to imply that any specificimplementation details are required. For example, any of the describedmodules and/or data structures may be combined or divided intosub-modules, sub-processes or other units of computer code or data asmay be required by a particular design or implementation. In thedrawings, specific arrangements or orderings of schematic elements maybe shown for ease of description. However, the specific ordering orarrangement of such elements is not meant to imply that a particularorder or sequence of processing, or separation of processes, is requiredin all embodiments. In general, schematic elements used to representinstruction blocks or modules may be implemented using any suitable formof machine-readable instruction, and each such instruction may beimplemented using any suitable programming language, library,application-programming interface (API), and/or other softwaredevelopment tools or frameworks. Similarly, schematic elements used torepresent data or information may be implemented using any suitableelectronic arrangement or data structure. Further, some connections,relationships or associations between elements may be simplified or notshown in the drawings so as not to obscure the disclosure. Thisdisclosure is to be considered as exemplary and not restrictive incharacter, and all changes and modifications that come within the spiritof the disclosure are desired to be protected.

What is claimed is:
 1. An iris biometric access control systemcomprising: one or more non-transitory machine readable storage media,and, embodied in the one or more non-transitory machine readable storagemedia a plurality of modules comprising: an iris image capture moduleto: by a face imager, detect the presence of a human face in a capturezone defined at least in part by a field of view of the face imager; inresponse to detection of the human face in the capture zone, align alens of an iris imager with an iris of the detected human face; operatean illuminator to illuminate the iris; and operate the iris imager toproduce a plurality of digital images of the iris, wherein theilluminator is operated to vary illumination of the iris synchronouslywith the frame rate of the iris imager to capture the plurality ofdigital images in rapid succession through the capture zone; and an irisimage processing and matching module to: select one or more of the irisimages for matching; extract a usable portion from each of the selectediris images; compare the extracted portion of each of the selected irisimages to a reference iris image; in response to the comparison of theextracted portions of the selected images and the reference image,operate an access control mechanism; at least one of the plurality ofmodules substantially synchronizing pulsed illumination by theilluminator and iris image capture by the iris imager using a focalsweep technique.
 2. The iris biometric access control system of claim 1,wherein the iris image capture module is to align the iris imager withthe iris of the detected human face by operating a motor.
 3. The irisbiometric access control system of claim 1, wherein the iris imagecapture module is to substantially synchronously operate the illuminatorand the iris imager to produce the plurality of digital images of theiris.
 4. A door lock assembly comprising: a housing, and, supported bythe housing: a door lock mechanism; and an iris biometric recognitionmodule in communication with the door lock mechanism to: detect thepresence of a human face in a capture zone defined at least in part by afield of view; align the lens of an iris imager with an iris of thehuman face; operate an illuminator to illuminate the iris; produce aplurality of digital images of the iris, wherein the illuminator isoperated to vary illumination of the iris synchronously with the framerate of the iris imager to capture the plurality of digital images inrapid succession through the capture zone; select one or more of theiris images for matching; extract a usable portion from each of theselected iris images; compare the extracted portion of each of theselected iris images to a reference iris image; in response to thecomparison of the extracted portions of the selected images and thereference image, operate the door lock mechanism; and substantiallysynchronize pulsed illumination by the illuminator and iris imagecapture by the imager using a focal sweep technique.
 5. The door lockassembly of claim 4, comprising a cover coupled to the housing, whereinthe cover and the housing define an interior region, and the irisbiometric recognition module is disposed within the interior region. 6.The door lock assembly of claim 5, wherein the cover comprises a windowpositioned adjacent the iris biometric recognition module and the windowis made of a material that is transparent to infrared light.
 7. The doorlock assembly of claim 4, wherein the iris biometric recognition modulecomprises a power supply, and powered by the power supply: an irisimager assembly and an iris imager control module in communication withthe iris imager assembly.
 8. The door lock assembly of claim 7,comprising a pivot support and an electric motor coupled to the pivotsupport by a pivot linkage, wherein the iris biometric recognitionmodule is supported by the pivot member.
 9. The door lock assembly ofclaim 8, wherein the iris imager assembly comprises an infraredilluminator and a narrow field of view imager adjacent the infraredilluminator.
 10. The door lock assembly of claim 9, wherein the irisimager assembly comprises a baffle disposed between the infraredilluminator and the narrow field of view imager.
 11. The door lockassembly of claim 7, comprising a face imager assembly supported by thehousing, wherein the face imager assembly comprises a wide field of viewimager and an infrared illuminator adjacent the wide field of viewimager.
 12. The door lock assembly of claim 4, comprising a power supplysupported by the housing, wherein the power supply is operably coupledto the door lock mechanism and the iris biometric recognition module.13. The door lock assembly of claim 4, comprising a handle supported bythe housing, wherein the handle is operably coupled to the door lockmechanism.
 14. A method for operating a door lock in response to irisbiometric recognition, the method performed by a door lock assembly, themethod comprising: detecting a human subject approaching the door lock,and, while the human subject is approaching the door lock: operating aface imager assembly to determine the location of the human subject'sface; operating an illuminator to illuminate an iris of an eye of thehuman subject; operating an iris imager assembly to capture a pluralityof iris images in rapid succession, wherein the illuminator is operableto vary illumination of the iris synchronously with the frame rate ofthe iris imager assembly, each of the iris images depicting at least aportion of the iris of the human subject; selecting an iris image of theplurality of iris images; comparing at least a portion of the selectediris image to a reference image; and in response to the comparison of atleast a portion of the selected iris image to the reference image,operating the door lock; and substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager assembly using a focal sweep technique.
 15. The method of claim14, wherein operating the face imager assembly comprises operating aninfrared illuminator of the face imager assembly and operating a widefield of view imager of the face imager assembly.
 16. The method ofclaim 14, wherein operating the iris imager assembly comprisescoordinating the operation a plurality of infrared illuminators of theiris imager assembly with the operation of an iris imager of the irisimager assembly.
 17. The method of claim 14, comprising operating theface imager assembly in response to the human subject being detected inthe range of at least about forty-five centimeters away from the doorlock.
 18. The iris biometric access control system of claim 1, whereinsubstantially synchronizing pulsed illumination by the illuminator andiris image capture by the iris imager using a focal sweep technique,comprises substantially synchronizing pulsed illumination by theilluminator and iris image capture by the iris imager using the focalsweep technique by varying the light intensity of the pulsedillumination.
 19. The iris biometric access control system of claim 18,wherein substantially synchronizing pulsed illumination by theilluminator and iris image capture by the iris imager using the focalsweep technique by varying the light intensity of the pulsedillumination, comprises substantially synchronizing pulsed illuminationby the illuminator and iris image capture by the iris imager using thefocal sweep technique by varying the light intensity of the pulsedillumination during strobing.
 20. The iris biometric access controlsystem of claim 18, wherein substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager using the focal sweep technique by varying the light intensity ofthe pulsed illumination, comprises substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager using the focal sweep technique by varying the light intensity ofthe pulsed illumination to maintain a predetermined signal to noiseratio.
 21. The iris biometric access control system of claim 1, whereinsubstantially synchronizing pulsed illumination by the illuminator andiris image capture by the iris imager using a focal sweep technique,comprises substantially synchronizing pulsed illumination by theilluminator and iris image capture by the iris imager using the focalsweep technique while an average irradiance of the illumination sourceremains below a safety threshold.
 22. The iris biometric access controlsystem of claim 1, wherein substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager using a focal sweep technique, comprises substantiallysynchronizing pulsed illumination by the illuminator and iris imagecapture by the iris imager assembly using the focal sweep technique toaccommodate a possibility that the subject may be in motion.
 23. Thedoor lock assembly of claim 4, wherein substantially synchronize pulsedillumination by the illuminator and iris image capture by the irisimager using a focal sweep technique, comprises substantiallysynchronize pulsed illumination by the illuminator and iris imagecapture by the iris imager using the focal sweep technique by varyingthe light intensity of the pulsed illumination.
 24. The door lockassembly of claim 23, wherein substantially synchronize pulsedillumination by the illuminator and iris image capture by the irisimager using the focal sweep technique by varying the light intensity ofthe pulsed illumination, comprises substantially synchronize pulsedillumination by the illuminator and iris image capture by the irisimager using the focal sweep technique by varying the light intensity ofthe pulsed illumination during strobing.
 25. The door lock assembly ofclaim 23, wherein substantially synchronize pulsed illumination by theilluminator and iris image capture by the iris imager using the focalsweep technique by varying the light intensity of the pulsedillumination, comprises substantially synchronize pulsed illumination bythe illuminator and iris image capture by the iris imager using thefocal sweep technique by varying the light intensity of the pulsedillumination to maintain a predetermined signal to noise ratio.
 26. Thedoor lock assembly of claim 4, wherein substantially synchronize pulsedillumination by the illuminator and iris image capture by the irisimager using a focal sweep technique, comprises substantiallysynchronize pulsed illumination by the illuminator and iris imagecapture by the iris imager using the focal sweep technique while anaverage irradiance of the illumination source remains below a safetythreshold.
 27. The door lock assembly of claim 4, wherein substantiallysynchronize pulsed illumination by the illuminator and iris imagecapture by the iris imager using a focal sweep technique, comprisessubstantially synchronize pulsed illumination by the illuminator andiris image capture by the iris imager assembly using the focal sweeptechnique to accommodate a possibility that the subject may be inmotion.
 28. The method of claim 14, wherein substantially synchronizingpulsed illumination by the illuminator and iris image capture by theiris imager assembly using a focal sweep technique, comprisessubstantially synchronizing pulsed illumination by the illuminator andiris image capture by the iris imager assembly using the focal sweeptechnique by varying the light intensity of the pulsed illumination. 29.The method of claim 28, wherein substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager assembly using the focal sweep technique by varying the lightintensity of the pulsed illumination, comprises substantiallysynchronizing pulsed illumination by the illuminator and iris imagecapture by the iris imager assembly using the focal sweep technique byvarying the light intensity of the pulsed illumination during strobing.30. The method of claim 28, wherein substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager assembly using the focal sweep technique by varying the lightintensity of the pulsed illumination, comprises substantiallysynchronizing pulsed illumination by the illuminator and iris imagecapture by the iris imager assembly using the focal sweep technique byvarying the light intensity of the pulsed illumination to maintain apredetermined signal to noise ratio.
 31. The method of claim 14, whereinsubstantially synchronizing pulsed illumination by the illuminator andiris image capture by the iris imager assembly using a focal sweeptechnique, comprises substantially synchronizing pulsed illumination bythe illuminator and iris image capture by the iris imager assembly usingthe focal sweep technique while an average irradiance of theillumination source remains below a safety threshold.
 32. The method ofclaim 14, wherein substantially synchronizing pulsed illumination by theilluminator and iris image capture by the iris imager assembly using afocal sweep technique, comprises substantially synchronizing pulsedillumination by the illuminator and iris image capture by the irisimager assembly using the focal sweep technique to accommodate apossibility that the subject may be in motion.
 33. An iris biometricaccess control system, comprising: one or more non-transitory machinereadable storage media, and, embodied in the one or more non-transitorymachine readable storage media a plurality of modules comprising: aniris image capture module to: by a face imager, detect the presence of ahuman face in a capture zone defined at least in part by a field of viewof the face imager; in response to detection of the human face in thecapture zone, align a lens of an iris imager with an iris of thedetected human face; operate an illuminator to illuminate the iris; andoperate the iris imager to produce a plurality of digital images of theiris, wherein the illuminator is operated to vary illumination of theiris synchronously with the frame rate of the iris imager to capture theplurality of digital images in rapid succession through the capturezone; and an iris image processing and matching module to: select one ormore of the iris images for matching; extract a usable portion from eachof the selected iris images; compare the extracted portion of each ofthe selected iris images to a reference iris image; and in response tothe comparison of the extracted portions of the selected images and thereference image, operate an access control mechanism; at least one ofthe plurality of modules substantially synchronizing pulsed illuminationand iris image capture using a focal sweep technique by varying lightintensity of the pulsed illumination during strobing to maintain apredetermined signal to noise ratio.
 34. The iris biometric accesscontrol system of claim 33, wherein substantially synchronizing pulsedillumination and iris image capture using the focal sweep technique,comprises substantially synchronizing pulsed illumination and iris imagecapture using the focal sweep technique while an average irradiance ofthe illumination source remains below a safety threshold.
 35. The irisbiometric access control system of 34, wherein substantiallysynchronizing pulsed illumination and iris image capture using the focalsweep technique, comprises substantially synchronizing pulsedillumination and iris image capture using the focal sweep technique toaccommodate a possibility that the subject may be in motion.